v_i_o_l_a<p>for F, A, I, and R there are several <a href="https://openbiblio.social/tags/DataProtection" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DataProtection</span></a> measures available. <a href="https://openbiblio.social/tags/OpenScience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>OpenScience</span></a> <a href="https://openbiblio.social/tags/RDM" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>RDM</span></a> <a href="https://openbiblio.social/tags/FAIRprinciples" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>FAIRprinciples</span></a> <a href="https://openbiblio.social/tags/OSDMA25" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>OSDMA25</span></a></p>
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#FAIRprinciples
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WiNoDa Knowledge Lab<p>👩💻 𝒲𝒾𝒩𝑜𝒟𝒶 ℒ𝒶𝒷 𝒥𝑜𝓊𝓇𝓃𝒶𝓁 🗞️</p><p>Read today about:<br>🔸 Persistent Identifiers for physical objects<br>🔸 Challenges of PIDs<br>🔸 Opportunities of PIDs<br>🔸 Citing PIDs</p><p><a href="https://winoda.de/en/2025/10/17/persistent-identifiers-pid-for-physical-objects/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">winoda.de/en/2025/10/17/persis</span><span class="invisible">tent-identifiers-pid-for-physical-objects/</span></a></p><p><a href="https://nfdi.social/tags/PID" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>PID</span></a> <a href="https://nfdi.social/tags/Article" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Article</span></a> <a href="https://nfdi.social/tags/Blog" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Blog</span></a> <a href="https://nfdi.social/tags/persistentidentifier" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>persistentidentifier</span></a> <a href="https://nfdi.social/tags/WiNoDa" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>WiNoDa</span></a> <a href="https://nfdi.social/tags/FAIRprinciples" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>FAIRprinciples</span></a></p>
OpenAIRE<p>Halfway through the OpenAIRE FAIR RDM Bootcamp for Data Stewards! 🚀</p><p>Over 70 participants from across Europe are turning FAIR and ethical data stewardship into action through collaboration and hands-on learning.</p><p>From planning and ethics to FAIR workflows, participants are mastering the full research lifecycle!</p><p><a href="https://mastodon.social/tags/OpenAIRE" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>OpenAIRE</span></a> <a href="https://mastodon.social/tags/FAIRdata" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>FAIRdata</span></a> <a href="https://mastodon.social/tags/RDM" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>RDM</span></a> <a href="https://mastodon.social/tags/OpenScience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>OpenScience</span></a> <a href="https://mastodon.social/tags/DataStewardship" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DataStewardship</span></a> <a href="https://mastodon.social/tags/EthicalResearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>EthicalResearch</span></a> <a href="https://mastodon.social/tags/FAIRprinciples" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>FAIRprinciples</span></a></p>
Heidi Seibold<p>Where do people publish images such that they are citable, FAIR and browsable?</p><p>I‘d like to publish my drawings under a CC-BY license for reuse but I am struggling finding a good place for that.</p><p><a href="https://fosstodon.org/tags/FAIRprinciples" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>FAIRprinciples</span></a></p>
JCLS<p><a href="https://fedihum.org/tags/DH2025" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DH2025</span></a>: Steffen Pielström, Kerstin Jung & Patrick Helling put the SPP <a href="https://fedihum.org/tags/CLS" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>CLS</span></a> projects to the test, examining their level of <a href="https://fedihum.org/tags/FAIRness" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>FAIRness</span></a> as a case study to assess how equal automated FAIRness tests are. <br><a href="https://fedihum.org/tags/FAIR" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>FAIR</span></a> <a href="https://fedihum.org/tags/FAIRprinciples" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>FAIRprinciples</span></a></p>
nf-core<p>Pipeline release! nf-core/drugresponseeval v1.1.0 - Drugresponseeval 1.1.0 - Humongous Zapdos!</p><p>Please see the changelog: <a href="https://github.com/nf-core/drugresponseeval/releases/tag/1.1.0" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">github.com/nf-core/drugrespons</span><span class="invisible">eeval/releases/tag/1.1.0</span></a></p><p><a href="https://mstdn.science/tags/celllines" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>celllines</span></a> <a href="https://mstdn.science/tags/crossvalidation" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>crossvalidation</span></a> <a href="https://mstdn.science/tags/deeplearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>deeplearning</span></a> <a href="https://mstdn.science/tags/drugresponse" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>drugresponse</span></a> <a href="https://mstdn.science/tags/drugresponseprediction" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>drugresponseprediction</span></a> <a href="https://mstdn.science/tags/drugs" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>drugs</span></a> <a href="https://mstdn.science/tags/fairprinciples" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>fairprinciples</span></a> <a href="https://mstdn.science/tags/generalization" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>generalization</span></a> <a href="https://mstdn.science/tags/hyperparametertuning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>hyperparametertuning</span></a> <a href="https://mstdn.science/tags/machinelearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>machinelearning</span></a> <a href="https://mstdn.science/tags/randomizationtests" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>randomizationtests</span></a> <a href="https://mstdn.science/tags/robustnessassessment" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>robustnessassessment</span></a> <a href="https://mstdn.science/tags/training" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>training</span></a> <a href="https://mstdn.science/tags/nfcore" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>nfcore</span></a> <a href="https://mstdn.science/tags/openscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>openscience</span></a> <a href="https://mstdn.science/tags/nextflow" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>nextflow</span></a> <a href="https://mstdn.science/tags/bioinformatics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>bioinformatics</span></a></p>
Bibliothèque Diderot de Lyon<p>📢Besoin de faire un Plan de Gestion de données pour votre projet de recherches ? Venez ce 19/05 17h à la <a href="https://social.sciences.re/tags/formation" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>formation</span></a> "Le plan de gestion de données du projet de recherche (PGD)" à la BDL ➡️ <a href="https://www.bibliotheque-diderot.fr/formations/le-plan-de-gestion-de-donnees-du-projet-de-recherche-pgd" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">bibliotheque-diderot.fr/format</span><span class="invisible">ions/le-plan-de-gestion-de-donnees-du-projet-de-recherche-pgd</span></a><br>Évènement PrintempsDeLaDonnée 2025 <a href="https://social.sciences.re/tags/PDLD2025" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>PDLD2025</span></a><br><a href="https://social.sciences.re/tags/openscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>openscience</span></a> <a href="https://social.sciences.re/tags/datamanagement" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>datamanagement</span></a> <a href="https://social.sciences.re/tags/DMP" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DMP</span></a> <a href="https://social.sciences.re/tags/DataManagementPlan" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DataManagementPlan</span></a> <a href="https://social.sciences.re/tags/FAIRprinciples" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>FAIRprinciples</span></a> <a href="https://social.sciences.re/tags/DMPOpidor" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DMPOpidor</span></a> <a href="https://social.sciences.re/tags/Lyon" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Lyon</span></a> <a href="https://social.sciences.re/tags/DATALystE" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DATALystE</span></a></p>
SPECSY.Photoelectrochemistry<p>A prominent example of what can happen if institutions are dependent on commercial enterprises sitting in the USA: The Trump administration made Microsoft block the email account of the <a href="https://xn--baw-joa.social/tags/ICC" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ICC</span></a> prosecutor:</p><p><a href="https://apnews.com/article/icc-trump-sanctions-karim-khan-court-a4b4c02751ab84c09718b1b95cbd5db3" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">apnews.com/article/icc-trump-s</span><span class="invisible">anctions-karim-khan-court-a4b4c02751ab84c09718b1b95cbd5db3</span></a></p><p>Given this recent example and the circumstance that this administration is in a constant quarrel with scientific institutions and also science in general, it is quite scary how dependent many - not all - German universities are for their core IT infrastructure on Microsoft services.</p><p>I hope this is a wake-up call for the IT service departments of our universities? We are increasingly encouraged to publish scientific findings (data, articles) according to <a href="https://xn--baw-joa.social/tags/FAIRPrinciples" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>FAIRPrinciples</span></a> in <a href="https://xn--baw-joa.social/tags/OpenScience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>OpenScience</span></a> , but shouldn't we also think more about the vulnerability of our whole workflow, if the underlying IT can be shut down simply by an order of someone on the other side of the planet? Open alternatives do exist!</p><p><a href="https://xn--baw-joa.social/tags/FOSS" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>FOSS</span></a> <a href="https://xn--baw-joa.social/tags/opensource" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>opensource</span></a> <a href="https://xn--baw-joa.social/tags/linux" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>linux</span></a></p>
WiNoDa Knowledge Lab<p>🔊 𝗘𝗮𝗴𝗲𝗿 𝘁𝗼 𝗲𝘅𝗽𝗹𝗼𝗿𝗲 𝗢𝗽𝗲𝗻 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗳𝗼𝗿 𝗼𝗯𝗷𝗲𝗰𝘁-𝗯𝗮𝘀𝗲𝗱 𝗿𝗲𝘀𝗲𝗮𝗿𝗰𝗵?</p><p>In an upcoming <a href="https://nfdi.social/tags/WiNoDa" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>WiNoDa</span></a> webinar, we will illustrate how the 𝗙𝗔𝗜𝗥 (Findable, Accessible, Interoperable, Reusable) and 𝗖𝗔𝗥𝗘 (Collective Benefit, Authority to Control, Responsibility, Ethics) 𝗽𝗿𝗶𝗻𝗰𝗶𝗽𝗹𝗲𝘀 can transform your research — making it more 𝗮𝗰𝗰𝗲𝘀𝘀𝗶𝗯𝗹𝗲, 𝗲𝘁𝗵𝗶𝗰𝗮𝗹, and 𝗶𝗺𝗽𝗮𝗰𝘁𝗳𝘂𝗹.</p><p>Join us online on May 20th!</p><p>👉 𝗥𝗲𝗴𝗶𝘀𝘁𝗲𝗿 𝗻𝗼𝘄: winoda.de/en/event/webinar-open-science-fair-and-care/</p><p><a href="https://nfdi.social/tags/OpenScience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>OpenScience</span></a> <a href="https://nfdi.social/tags/FAIRPrinciples" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>FAIRPrinciples</span></a> <a href="https://nfdi.social/tags/CAREPrinciples" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>CAREPrinciples</span></a></p>
ing.grid<p>📢 We’re looking forward to participating in the Mini-Conference on Open and FAIR Practices in Natural & Engineering Sciences, taking place 22–23 May in Utrecht.</p><p>🔗 <a href="https://community.data.4tu.nl/2025/02/05/open-and-fair-in-nes/" rel="nofollow noopener" target="_blank"><span class="invisible">https://</span><span class="ellipsis">community.data.4tu.nl/2025/02/</span><span class="invisible">05/open-and-fair-in-nes/</span></a></p><p> <a href="https://nfdi.social/tags/FAIRdata" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>FAIRdata</span></a> <a href="https://nfdi.social/tags/OpenResearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>OpenResearch</span></a> <a href="https://nfdi.social/tags/inggrid" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>inggrid</span></a> <a href="https://nfdi.social/tags/FAIRprinciples" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>FAIRprinciples</span></a> <a href="https://nfdi.social/tags/4TUResearchData" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>4TUResearchData</span></a></p>
NFDI<p>New Whitepaper published: "Measuring the Value of (Research) Data" 📊📚</p><p>Data is more than just the "new oil"—it’s a unique economic asset with special characteristics that make its value challenging to measure. But how can businesses and research institutions quantify the actual value of their data?</p><p>📄 Read the full whitepaper here: <a href="https://zenodo.org/records/14944087" rel="nofollow noopener" target="_blank"><span class="invisible">https://</span><span class="">zenodo.org/records/14944087</span><span class="invisible"></span></a></p><p><a href="https://nfdi.social/tags/ResearchData" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ResearchData</span></a> <a href="https://nfdi.social/tags/DataEconomy" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DataEconomy</span></a> <a href="https://nfdi.social/tags/DataValue" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DataValue</span></a> <a href="https://nfdi.social/tags/FAIRPrinciples" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>FAIRPrinciples</span></a> <a href="https://nfdi.social/tags/Innovation" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Innovation</span></a> <a href="https://nfdi.social/tags/NFDI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>NFDI</span></a> <a href="https://nfdi.social/tags/BusinessValue" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>BusinessValue</span></a> <a href="https://nfdi.social/tags/DataSharing" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DataSharing</span></a></p>
(((@amarois)))<p>[Reading] passionnant, et si bien écrit : "Di Cosmo R., Granger S., Hinsen K., Jullien N., Le Berre D., Louvet V., Maumet C., Maurice C., Monat R. et Rougier N. P., « CODE beyond FAIR »=> <a href="https://inria.hal.science/hal-04930405" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">inria.hal.science/hal-04930405</span><span class="invisible"></span></a><br><a href="https://mamot.fr/tags/FAIRprinciples" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>FAIRprinciples</span></a> <a href="https://mamot.fr/tags/researchdatamanagement" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>researchdatamanagement</span></a> <a href="https://mamot.fr/tags/openscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>openscience</span></a> <a href="https://mamot.fr/tags/researchsoftwares" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>researchsoftwares</span></a> <a href="https://mamot.fr/tags/reproductibility" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>reproductibility</span></a> <a href="https://mamot.fr/tags/science" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>science</span></a> <a href="https://mamot.fr/tags/FLOSS" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>FLOSS</span></a> <a href="https://mamot.fr/tags/digitalpreservation" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>digitalpreservation</span></a></p>
(((@amarois)))<p>[veille] <a href="https://mamot.fr/tags/ebooks" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ebooks</span></a> Kosmopoulos Chr. et Schöpfel J., "Publier, partager, réutiliser les données de la recherche : les data papers et leurs enjeux" Pr. Univ. du Septentrion=> <a href="https://www.septentrion.com/fr/book/?GCOI=27574100316700" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">septentrion.com/fr/book/?GCOI=</span><span class="invisible">27574100316700</span></a><br><a href="https://mamot.fr/tags/openscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>openscience</span></a> <a href="https://mamot.fr/tags/datapapers" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>datapapers</span></a> <a href="https://mamot.fr/tags/researchdatamanagement" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>researchdatamanagement</span></a> <a href="https://mamot.fr/tags/FAIRprinciples" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>FAIRprinciples</span></a> <a href="https://mamot.fr/tags/FAIRdata" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>FAIRdata</span></a> <a href="https://mamot.fr/tags/publishing" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>publishing</span></a></p>
DataCite<p>The INFLIBNET Centre, with financial support under DataCite's GAF, has made significant strides in promoting an <a href="https://openbiblio.social/tags/openscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>openscience</span></a> ecosystem with special reference to research data sharing & <a href="https://openbiblio.social/tags/PIDs" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>PIDs</span></a> in India. Read how this collaboration is transforming the Indian research landscape:<br><a href="https://doi.org/10.5438/khj0-3784" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">doi.org/10.5438/khj0-3784</span><span class="invisible"></span></a></p><p><a href="https://openbiblio.social/tags/ResearchData" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ResearchData</span></a> <a href="https://openbiblio.social/tags/FAIRPrinciples" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>FAIRPrinciples</span></a> <a href="https://openbiblio.social/tags/PID" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>PID</span></a> <a href="https://openbiblio.social/tags/PersistenIdentifier" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>PersistenIdentifier</span></a> <br><span class="h-card" translate="no"><a href="https://qoto.org/@Mohamadmostafa" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>Mohamadmostafa</span></a></span></p>
Allyson Lister<p>Our <a href="https://fediscience.org/tags/FAIRsharingCommunityChampions" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>FAIRsharingCommunityChampions</span></a> <a href="https://fediscience.org/tags/MarkMcKerracher" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>MarkMcKerracher</span></a> has created a short video "Data tips: <a href="https://fediscience.org/tags/FAIR" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>FAIR</span></a> principles in 60 seconds" as part of his work at the SDS repository at <a href="https://fediscience.org/tags/UniversityofOxford" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>UniversityofOxford</span></a>, where he also recommends <span class="h-card" translate="no"><a href="https://fediscience.org/@fairsharing" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>fairsharing</span></a></span> </p><p>Take a look at <a href="https://doi.org/10.25446/oxford.28323506.v2" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">doi.org/10.25446/oxford.283235</span><span class="invisible">06.v2</span></a>, and at the entire series of videos is available at <a href="https://portal.sds.ox.ac.uk/SDS_self_help" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">portal.sds.ox.ac.uk/SDS_self_h</span><span class="invisible">elp</span></a></p><p>See also <a href="https://fairsharing.org/educational#fair" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">fairsharing.org/educational#fa</span><span class="invisible">ir</span></a></p><p><a href="https://fediscience.org/tags/FAIRprinciples" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>FAIRprinciples</span></a></p>
Digital Research Academy<p>We're excited to be supporting the upcoming<br>✨ BERD Unconference Workshop Series ✨ </p><p>Meet peers and collaborate: Build connections and collaborate with like-minded peers from business, economics, and related research fields on <a href="https://mastodon.social/tags/FAIRprinciples" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>FAIRprinciples</span></a>, <a href="https://mastodon.social/tags/AI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AI</span></a>, data and more.</p><p><a href="https://www.berd-nfdi.de/berd-academy/berd-unconference-workshop-series/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">berd-nfdi.de/berd-academy/berd</span><span class="invisible">-unconference-workshop-series/</span></a></p>
nf-core<p>Pipeline release! nf-core/drugresponseeval v1.0.0 - 1.0.0!</p><p>Please see the changelog: <a href="https://github.com/nf-core/drugresponseeval/releases/tag/1.0.0" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">github.com/nf-core/drugrespons</span><span class="invisible">eeval/releases/tag/1.0.0</span></a></p><p><a href="https://mstdn.science/tags/celllines" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>celllines</span></a> <a href="https://mstdn.science/tags/crossvalidation" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>crossvalidation</span></a> <a href="https://mstdn.science/tags/deeplearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>deeplearning</span></a> <a href="https://mstdn.science/tags/drugresponse" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>drugresponse</span></a> <a href="https://mstdn.science/tags/drugresponseprediction" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>drugresponseprediction</span></a> <a href="https://mstdn.science/tags/drugs" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>drugs</span></a> <a href="https://mstdn.science/tags/fairprinciples" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>fairprinciples</span></a> <a href="https://mstdn.science/tags/generalization" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>generalization</span></a> <a href="https://mstdn.science/tags/hyperparametertuning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>hyperparametertuning</span></a> <a href="https://mstdn.science/tags/machinelearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>machinelearning</span></a> <a href="https://mstdn.science/tags/randomizationtests" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>randomizationtests</span></a> <a href="https://mstdn.science/tags/robustnessassessment" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>robustnessassessment</span></a> <a href="https://mstdn.science/tags/training" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>training</span></a> <a href="https://mstdn.science/tags/nfcore" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>nfcore</span></a> <a href="https://mstdn.science/tags/openscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>openscience</span></a> <a href="https://mstdn.science/tags/nextflow" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>nextflow</span></a> <a href="https://mstdn.science/tags/bioinformatics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>bioinformatics</span></a></p>
Aneesh Sathe<p><strong>Domain Ontologies: Indispensable for Knowledge Graph Construction</strong></p><p>AI slop is all around and increasingly extraction of useful information will face difficulties as we start to feed more noise into the already noisy world of knowledge. We are in an era of unprecedented data abundance, yet this deluge of information often lacks the structure necessary to derive meaningful insights. <strong>Knowledge graphs (KGs), with their ability to represent entities and their relationships as interconnected nodes and edges, have emerged as a powerful tool for managing and leveraging complex data</strong>. However, the efficacy of a KG is critically dependent on the underlying structure provided by domain ontologies. These ontologies, which are formal, machine-readable conceptualizations of a specific field of knowledge, are not merely useful, but essential for the creation of robust and insightful KGs. Let’s explore the role that domain ontologies play in scaffolding KG construction, drawing on various fields such as AI, healthcare, and cultural heritage, to illuminate their importance.</p><a href="https://aneeshsathe.com/wp-content/uploads/2025/01/image-8.png" rel="nofollow noopener" target="_blank"></a><a href="https://en.wikipedia.org/wiki/Wassily_Kandinsky" rel="nofollow noopener" target="_blank">Vassily Kandinsky,</a> 1913 – Composition VII (1913)<br>According to Kandinsky, this is the most complex piece he ever painted.<p>At its core, an ontology is a <strong>formal representation of knowledge within a specific domain</strong>, providing a structured vocabulary and defining the semantic relationships between concepts. In the context of KGs, ontologies serve as the blueprint that defines the types of nodes (entities) and edges (relationships) that can exist within the graph. Without this foundational structure, a KG would be a mere collection of isolated data points with limited utility. The ontology ensures that the KG’s data is not only interconnected but also semantically interoperable. For example, in the biomedical domain, an ontology like the Chemical Entities of Biological Interest (ChEBI) provides a standardized way of representing molecules and their relationships, which is essential for building biomedical KGs. Similarly, in the cultural domain, an ontology provides a controlled vocabulary to define the entities, such as artworks, artists, and historical events, and their relationships, thus creating a consistent representation of cultural heritage information.</p><p>One of the primary reasons domain ontologies are crucial for KGs is their role in <strong>ensuring data consistency and interoperability</strong>. Ontologies provide unique identifiers and clear definitions for each concept, which helps in aligning data from different sources and avoiding ambiguities. Consider, for example, a healthcare KG that integrates data from various clinical trials, patient records, and research publications. Without a shared ontology, terms like “cancer” or “hypertension” may be interpreted differently across these data sets. The use of ontologies standardizes the representation of these concepts, thus allowing for effective integration and analysis. This not only enhances the accuracy of the KG but also makes the information more accessible and reusable. Furthermore, using ontologies that follow the FAIR (Findable, Accessible, Interoperable, Reusable) principles facilitates data integration, unification, and information sharing, essential for building robust KGs.</p><p>Moreover, ontologies <strong>facilitate the application of advanced AI methods to unlock new knowledge</strong>. They support both deductive reasoning to infer new knowledge and provide structured background knowledge for machine learning. In the context of drug discovery, for instance, a KG built on a biomedical ontology can help identify potential drug targets by connecting genes, proteins, and diseases through clearly defined relationships. This structured approach to data also enables the development of explainable AI models, which are critical in fields like medicine where the decision-making process must be transparent and interpretable. The ontology-grounded KGs can then be used to generate hypotheses that can be validated through manual review, in vitro experiments, or clinical studies, highlighting the utility of ontologies in translating complex data into actionable knowledge.</p><p>Despite their many advantages, domain ontologies are not without their challenges. One major hurdle is the <strong>lack of direct integration between data and ontologies</strong>, meaning that most ontologies are abstract knowledge models not designed to contain or integrate data. This necessitates the use of (semi-)automated approaches to integrate data with the ontological knowledge model, which can be complex and resource-intensive. Additionally, the existence of multiple ontologies within a domain can lead to semantic inconsistencies that impede the construction of holistic KGs. Integrating different ontologies with overlapping information may result in semantic irreconcilability, making it difficult to reuse the ontologies for the purpose of KG construction. Careful planning is therefore required when choosing or building an ontology.</p><p>As we move forward, the development of <strong>integrated, holistic solutions</strong> will be crucial to unlocking the full potential of domain ontologies in KG construction. This means creating methods for integrating multiple ontologies, ensuring data quality and credibility, and focusing on semantic expansion techniques to leverage existing resources. Furthermore, there needs to be a greater emphasis on creating ontologies with the explicit purpose of instantiating them, and storing data directly in graph databases. The integration of expert knowledge into KG learning systems, by using ontological rules, is crucial to ensure that KGs not only capture data, but also the logical patterns, inferences, and analytic approaches of a specific domain.</p><p>Domain ontologies will prove to be the key to building robust and useful KGs. They provide the necessary structure, consistency, and interpretability that enables AI systems to extract valuable insights from complex data. By understanding and addressing the challenges associated with ontology design and implementation, we can harness the power of KGs to solve complex problems across diverse domains, from healthcare and science to culture and beyond. The future of knowledge management lies not just in the accumulation of data but in the development of intelligent, ontologically-grounded systems that can bridge the gap between information and meaningful understanding. </p><p><strong>References </strong></p><ol><li>Al-Moslmi, T., El Alaoui, I., Tsokos, C.P., & Janjua, N. (2021). Knowledge graph construction approaches: A survey of recent research works. <em>arXiv preprint</em>. <a href="https://arxiv.org/abs/2011.00235" rel="nofollow noopener" target="_blank">https://arxiv.org/abs/2011.00235</a></li><li>Chandak, P., Huang, K., & Zitnik, M. (2023). PrimeKG: A multimodal knowledge graph for precision medicine. <em>Scientific Data</em>. <a href="https://www.nature.com/articles/s41597-023-01960-3" rel="nofollow noopener" target="_blank">https://www.nature.com/articles/s41597-023-01960-3</a></li><li>Gilbert, S., & others. (2024). Augmented non-hallucinating large language models using ontologies and knowledge graphs in biomedicine. <em>npj Digital Medicine</em>. <a href="https://www.nature.com/articles/s41746-024-01081-0" rel="nofollow noopener" target="_blank">https://www.nature.com/articles/s41746-024-01081-0</a></li><li>Guzmán, A.L., et al. (2022). Applications of Ontologies and Knowledge Graphs in Cancer Research: A Systematic Review. <em>Cancers, 14</em>(8), 1906. <a href="https://www.mdpi.com/2072-6694/14/8/1906" rel="nofollow noopener" target="_blank">https://www.mdpi.com/2072-6694/14/8/1906</a></li><li>Hura, A., & Janjua, N. (2024). Constructing domain-specific knowledge graphs from text: A case study on subprime mortgage crisis. <em>Semantic Web Journal</em>. <a href="https://www.semantic-web-journal.net/content/constructing-domain-specific-knowledge-graphs-text-case-study-subprime-mortgage-crisis" rel="nofollow noopener" target="_blank">https://www.semantic-web-journal.net/content/constructing-domain-specific-knowledge-graphs-text-case-study-subprime-mortgage-crisis</a></li><li>Kilicoglu, H., et al. (2024). Towards better understanding of biomedical knowledge graphs: A survey. <em>arXiv preprint</em>. <a href="https://arxiv.org/abs/2402.06098" rel="nofollow noopener" target="_blank">https://arxiv.org/abs/2402.06098</a></li><li>Noy, N.F., & McGuinness, D.L. (2001). Ontology Development 101: A Guide to Creating Your First Ontology. <em>Semantic Scholar</em>. <a href="https://www.semanticscholar.org/paper/Ontology-Development-101%3A-A-Guide-to-Creating-Your-Noy/c15cf32df98969af5eaf85ae3098df6d2180b637" rel="nofollow noopener" target="_blank">https://www.semanticscholar.org/paper/Ontology-Development-101%3A-A-Guide-to-Creating-Your-Noy/c15cf32df98969af5eaf85ae3098df6d2180b637</a></li><li>Taneja, S.B., et al. (2023). NP-KG: A knowledge graph for pharmacokinetic natural product-drug interaction discovery. <em>Journal of Biomedical Informatics</em>. <a href="https://www.sciencedirect.com/science/article/pii/S153204642300062X" rel="nofollow noopener" target="_blank">https://www.sciencedirect.com/science/article/pii/S153204642300062X</a></li><li>Zhao, X., & Han, Y. (2023). Architecture of Knowledge Graph Construction. <em>Semantic Scholar</em>. <a href="https://www.semanticscholar.org/paper/Architecture-of-Knowledge-Graph-Construction-Zhao-Han/dcd600619962d5c1f1cfa08a85d0be43a626b301" rel="nofollow noopener" target="_blank">https://www.semanticscholar.org/paper/Architecture-of-Knowledge-Graph-Construction-Zhao-Han/dcd600619962d5c1f1cfa08a85d0be43a626b301</a></li></ol><p><a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://aneeshsathe.com/tag/ai-in-healthcare/" target="_blank">#AIInHealthcare</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://aneeshsathe.com/tag/artificial-intelligence-2/" target="_blank">#ArtificialIntelligence</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://aneeshsathe.com/tag/biomedical-ontologies/" target="_blank">#BiomedicalOntologies</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://aneeshsathe.com/tag/cultural-heritage-data/" target="_blank">#CulturalHeritageData</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://aneeshsathe.com/tag/data-integration/" target="_blank">#DataIntegration</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://aneeshsathe.com/tag/data-interoperability/" target="_blank">#DataInteroperability</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://aneeshsathe.com/tag/domain-ontologies/" target="_blank">#DomainOntologies</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://aneeshsathe.com/tag/drug-discovery/" target="_blank">#DrugDiscovery</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://aneeshsathe.com/tag/explainable-ai/" target="_blank">#ExplainableAI</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://aneeshsathe.com/tag/fair-principles/" target="_blank">#FAIRPrinciples</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://aneeshsathe.com/tag/graph-databases/" target="_blank">#GraphDatabases</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://aneeshsathe.com/tag/knowledge-graphs/" target="_blank">#KnowledgeGraphs</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://aneeshsathe.com/tag/knowledge-management/" target="_blank">#KnowledgeManagement</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://aneeshsathe.com/tag/llms/" target="_blank">#LLMs</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://aneeshsathe.com/tag/ontology/" target="_blank">#Ontology</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://aneeshsathe.com/tag/ontology-design/" target="_blank">#OntologyDesign</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://aneeshsathe.com/tag/ontology-development/" target="_blank">#OntologyDevelopment</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://aneeshsathe.com/tag/ontology-driven-ai/" target="_blank">#OntologyDrivenAI</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://aneeshsathe.com/tag/semantic-relationships/" target="_blank">#SemanticRelationships</a> <a rel="nofollow noopener" class="hashtag u-tag u-category" href="https://aneeshsathe.com/tag/semantic-web/" target="_blank">#SemanticWeb</a></p>
Digital Research Academy<p>🎄 Day 21 of our DRAdvent Calendar! 🎄 </p><p>We teach <a href="https://mastodon.social/tags/ReproducibleResearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ReproducibleResearch</span></a> as well as the <a href="https://mastodon.social/tags/FAIRprinciples" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>FAIRprinciples</span></a>, so we also think about making our own training materials reproducible and FAIR.</p><p>DRA trainers <span class="h-card" translate="no"><a href="https://scholar.social/@toothFAIRy" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>toothFAIRy</span></a></span> and <span class="h-card" translate="no"><a href="https://fediscience.org/@lnnrtwttkhn" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>lnnrtwttkhn</span></a></span> made amazing slides on how create them using Quarto.</p><p><a href="https://lennartwittkuhn.com/dra-fair-teaching/#/title-slide" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">lennartwittkuhn.com/dra-fair-t</span><span class="invisible">eaching/#/title-slide</span></a></p>
(((@amarois)))<p>[ToRead] M. Le Béchec ; C. Gruson-Daniel ; C. Lascombes ; É. Schultz - Notebook and Open science: toward more FAIR play jdmdh:13428-Journal of Data Mining & Digital Humanities, 16 déc. 2024, Atelier Digit\_Hum=> <a href="https://doi.org/10.46298/jdmdh.13428" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">doi.org/10.46298/jdmdh.13428</span><span class="invisible"></span></a><br><a href="https://mamot.fr/tags/FAIRprinciples" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>FAIRprinciples</span></a> <a href="https://mamot.fr/tags/openscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>openscience</span></a> <a href="https://mamot.fr/tags/notebooks" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>notebooks</span></a> <a href="https://mamot.fr/tags/literateprogramming" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>literateprogramming</span></a> <a href="https://mamot.fr/tags/DH" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DH</span></a></p>
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