livellosegreto.it is one of the many independent Mastodon servers you can use to participate in the fediverse.
Livello Segreto è il social etico che ha rispetto di te e del tuo tempo.

Administered by:

Server stats:

1.2K
active users

#ontologies

0 posts0 participants0 posts today

TGDK is launching a Special Issue for Use-Case articles. They are interested in submissions describing use-cases (applications, events, products, services, etc.) that put research on Graph Data & Knowledge into practice. If you work on such initiatives, consider telling the community about them by submitting to the Special Issue!
Deadline is March 31, 2025.

drops.dagstuhl.de/entities/jou

@tgdkjournal #knowledgegraphs #semanticweb #ontologies #AI #neurosymbolicAI

drops.dagstuhl.deTGDK

The programme for the @DHdKonferenz (DhD2025) is out. Unfortunately, they did not want our Ontology (eXtreme) Design HandsOn workshop - which from my point of view might have been (highly) beneficial for the German #DH community...

DhD 2025 Programm: dhd2025.dig-hum.de/?page_id=8

eXtreme Design for DH Workshop: doi.org/10.5281/zenodo.1476043

#ontologies #digitalhumanities #semanticweb #AI @sourisnumerique @enorouzi @jonatan #lostOpportunity #knowledgegraphs

Continued thread

The paper “Contours of Knowledge: Epistemological Implications of Semantic Models in the Representation of the Art Exhibition Domain through the Lens of the OntoExhibit Ontology” by Nuria Rodríguez-Ortega highlights the development of the OntoExhibit ontology, which aims to redefine how art exhibitions are digitally represented. It emphasizes a post-anthropocentric approach, incorporating human and non-human agents, such as AI.

I released some updates for #ABECTO: github.com/fusion-jena/abecto/
ABECTO is a tool that compares #RDF data to spot errors 📑 and assess completeness 📏.
Recent changes:
➡️ adjusts result export for #Wikidata Mismatch Finder to changed format (phabricator.wikimedia.org/T313)
➡️ add reporting of qualifier mismatches to Wikidata Mismatch Finder export
➡️ suppress illegal empty external values in Wikidata Mismatch Finder export

@nightrose #DataQuality #Ontologies #KnowledgeGraphs

GitHubReleases · fusion-jena/abectoAn ABox Evaluation and Comparison Tool for Ontologies. - fusion-jena/abecto

📢 Call for Participation! With support from SmartEdge, ERCIM/W3C is hosting the #AIOTi Workshop on Semantic #Interoperability for #DigitalTwins at Inria Sophia Antipolis, France on 5-6 February 2025.
▶️ ercim.eu/events/aioti-workshop

Semantic Interoperability is the ability of computer systems to exchange data with a shared, unambiguous meaning. This is relevant to SmartEdge regarding the use of controlled vocabularies, taxonomies, and #ontologies in information modeling for the project's use cases.

Dynamic Retrieval Augmented Generation of Ontologies using Artificial Intelligence (DRAGON-AI) arxiv.org/abs/2312.10904 #bioinformatics #llms #ontologies

arXiv.orgDynamic Retrieval Augmented Generation of Ontologies using Artificial Intelligence (DRAGON-AI)Background: Ontologies are fundamental components of informatics infrastructure in domains such as biomedical, environmental, and food sciences, representing consensus knowledge in an accurate and computable form. However, their construction and maintenance demand substantial resources and necessitate substantial collaboration between domain experts, curators, and ontology experts. We present Dynamic Retrieval Augmented Generation of Ontologies using AI (DRAGON-AI), an ontology generation method employing Large Language Models (LLMs) and Retrieval Augmented Generation (RAG). DRAGON-AI can generate textual and logical ontology components, drawing from existing knowledge in multiple ontologies and unstructured text sources. Results: We assessed performance of DRAGON-AI on de novo term construction across ten diverse ontologies, making use of extensive manual evaluation of results. Our method has high precision for relationship generation, but has slightly lower precision than from logic-based reasoning. Our method is also able to generate definitions deemed acceptable by expert evaluators, but these scored worse than human-authored definitions. Notably, evaluators with the highest level of confidence in a domain were better able to discern flaws in AI-generated definitions. We also demonstrated the ability of DRAGON-AI to incorporate natural language instructions in the form of GitHub issues. Conclusions: These findings suggest DRAGON-AI's potential to substantially aid the manual ontology construction process. However, our results also underscore the importance of having expert curators and ontology editors drive the ontology generation process.

Eine Klasse für sich, ein klasse Werkzeug oder klassisch überschätzt? Welchen Nutzen bieten Ontologien für die sozialwissenschaftliche Forschung?

Diesen und weiteren Fragen gehe ich am 25.09.24 gemeinsam mit Kolleg*innen vom @bibb nach, im gleichnamigen thematischen Panel (organisiert von Michael Tiemann) auf der diesjährigen Sektionenkonferenz der DGS.

Ich freue mich auf den Austausch zu #KnowledgeGraphs und #Ontologies sowie auf inspirierende Antwortvorschläge zu unseren Fragen 🤗

I'm the FAIRsharing (fairsharing.org/) Content and Community Lead, and my main interest is in helping researchers enable FAIR data within the research data lifecycle. I also enjoy talking about #ontologies and #datastewardship

Do you have a data standard, database or data policy within your research domain that you are developing? Would you like to increase its findability to researchers? Add or claim its record with us! fairsharing.gitbook.io/fairsha

#introductions
#introduction

fairsharing.orgFAIRsharing