@petejones @HeidiSeibold I would always go for #Zenodo though. Their visibility is unchallenged and their longterm survival is more likely than that of the Knowledge Commons (Zenodo guarantees preservation for 20 years after the defunding of #CERN )
@MartinEscardo I know https://zenodo.org is in theory for data, but I uploaded text as well and I code could be uploaded, too. Might be helpful? By #CERN and part of #OpenAIRE - which based an a cursory look might itself offer a framework / funding? for a more specifically code-oriented solution. #zenodo
Was die Ahnen- und Familienforscher unter euch auch interessieren dürfte: Parallel zur Veröffentlichung der einzelnen Dokumente auf #Zenodo, wird unter https://kalliope-verbund.info/findingaid_index?fa.id=DE-611-BF-70963 permanent ein Index über Namen, Orte und Firmen gepflegt.
In late 2024, we launched a collaboration between The Carpentries and the Generalist Repository Ecosystem Initiative (GREI), aiming to explore how generalist data repositories such as #Dataverse, #Dryad, #Figshare, Mendeley Data, Open Science Framework, #Vivli, and #Zenodo might be more intentionally woven into the data skills we teach. 
In the process, we also asked ourselves some important questions: 
What would it look like if open data repositories weren’t just add-ons at the end of a workflow, but upfront teaching concepts in our lessons? How can we position generalist repositories as active components in retrieving and processing datasets? How can we give researchers the tools not just to write clean code, but to publish their work in ways that make it reusable and citable by others?
Learn about the important steps we have taken in this collaboration toward co-creating new lesson content: https://carpentries.org/blog/2025/06/update-on-the-carpentries-and-grei-collaboration/ 
NEW PAPER!
Non-Neutral by Design: Why Generative Models Cannot Escape Linguistic Training
https://papers.ssrn.com/abstract=5288307
No generative model is neutral. This paper argues that large language models are structurally shaped by their training corpus, embedding patterns of syntactic obedience and algorithmic authority from the start.
DOI: 10.5281/zenodo.15615901
Author: Agustin V. Startari (2025)
This is #OpenScience: The most viewed paper on #CERN's #Zenodo sounds like a conspiracy theory from the title, but surely would never get published any other way. Bravo for #OpenAccess...whether it has merit or not depends on the intellect of 1.2 million who viewed it.
Er zijn nogal wat repositories voor openbaar beschikbare onderzoeksdata, zoals DANS, #DataverseNL, en #Zenodo. Is er eigenlijk iets als WorldCat, zodat je alle bestaande onderzoeksdata-repositories kan doorzoeken? #FAIR #researchdata
#CienciaAbierta, #comunidades, #community, #science… Estas son algunas de las palabras que más se repiten en los títulos de nuestras publicaciones en #Zenodo.
Ya sistematizamos y pusimos a disposición más de 200 archivos y documentos que pueden ser de gran utilidad para nuestra comunidad.
Te invitamos a recorrer y explorar estos recursos: https://zenodo.org/communities/metadocencia/
Merging pull requests (dependancy bumps) and reserving #Zenodo DOIs from the departure gate. A shame I'm not being paid for this 
@Alejandro_P
You can find many contributions to #HMC_CON2025 in our #Zenodo Community:
https://zenodo.org/communities/hmc-conference-2025
#Autaxys #Research & Development Master #Plan (v1.0)
https://doi.org/10.5281/zenodo.15555539
I will begin hosting research outputs on #Zenodo via the "Autaxis and #Autology" community and hope to interest others in joining/participating: https://zenodo.org/communities/autaxys/
De nos jours, on exige de plus en plus la disponibilité du code (et les données) qui a servi pour une recherche, pour pouvoir la reproduire.
Et je découvre le dépôt #Zenodo https://zenodo.org/
Évidemment, c'est plus facile à dire qu'à faire. (Bibliothèques qui ont changé…) par exemple pour des raisons quantitatives (modèles de climat qui nécessitent des mois de calcul…)
So, zurück vom #UFFestival bin ich immer noch ganz begeistert bei der Nacharbeit. Die Slides stehen jetzt auf #Zenodo bereit:
Dungeons and Dashboards: Wie #ChatGPT #Personas zum Leben erweckt: https://doi.org/10.5281/zenodo.15384622 #DiSEA #Dashboard #Moodle
Bildungsplattformen schönrechnen: https://doi.org/10.5281/zenodo.15462970
Bildung findet Stadt: #FutureSkills vor der Haustür: https://doi.org/10.5281/zenodo.15396267 #DLC #Lernorte
Alle Infos und Links zu Aufzeichnungen unter https://secret-cow-level.de/wordpress/about/publikationen/
Warme Tage, kühle Entscheidungen: Unser Metadaten-Entscheidungsbaum ist da! 
Braucht ihr Orientierung im Dschungel der #Metadaten? Unser neuer Entscheidungsbaum bietet einen spielerischen Einstieg und praktische Unterstützung – jetzt in unserer Zenodo-Community!
Ressourcen der SODa Community auf Zenodo!
Ihr möchtet Eure Datenkompetenz erweitern & von dem Fachwissen einer lebendigen Community profitieren?
Dann werft einen Blick auf die vielfältigen Ressourcen, die wir auf Zenodo zusammengestellt haben: https://zenodo.org/communities/soda/?utm_campaign=coschedule&utm_source=mastodon&utm_medium=SODa%40fedihum.org
Hier findet Ihr Präsentationen aus unseren Veranstaltungen, Leitfäden, Best Practices & mehr – alles, rund um die Themen Sammlungen, Objekte & Datenkompetenzen.
#DataLiteracy #SODaZentrum #Zenodo #Sammlungen #OER
As it seems, using Lego aesthetics is legally doubtful: https://www.lego.com/en-de/legal/notices-and-policies/fair-play?locale=en-de
How do I know? Well, some here might remember the wonderful image collection of Lego minifigures for research data management on Zenodo: https://zenodo.org/records/11147887 - the access is now restricted, and I asked for the reason. So, yes, you may use such images for non-commercial, educational purposes - with a note. Yet, be careful. I will certainly change my chapter cover slides.
Is #Zenodo ok? I have clicked into maybe 10 different "communities" at random, because I'm looking for an example to show someone who is choosing a platform to deposit some interim research products, and all of them have a message like this:
This could take the form of setting up repositories (#github/ #zenodo) etc that store the prompts used and the output received from the #LLMs. For example, if one were to use a chatbot to develop the plan for a scientific report and/or the first draft, the prompts and the output should be made public as research methods & supplementary material.
Differencing tools could then be automatically deployed to show how the final product changed to the #LLM output that was first received or even ...
This could take the form of setting up repositories (#github/ #zenodo) etc that store the prompts used and the output received from the #LLMs. For example, if one were to use a chatbot to develop the plan for a scientific report and/or the first draft, the prompts and the output should be made public as research methods & supplementary material.
Differencing tools could then be automatically deployed to show how the final product changed to the #LLM output that was first received, or even ...
This could take the form of setting up repositories (#github/ #zenodo) etc that store the prompts used and the output received from the #LLMs. For example, if one were to use a chatbot to develop the plan for a scientific report and/or the first draft, the prompts and the output should be made public as research methods & supplementary material.
Differencing tools could then be automatically deployed to show how the final product changed to the #LLM output that was first received, or even ...
