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NFDI4DSO: Towards a BFO Compliant Ontology for Data Science

Artificial Intelligence 2024-08-19 v1 Databases
Authors: Genet Asefa Gesese , Jörg Waitelonis , Zongxiong Chen , Sonja Schimmler , Harald Sack
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Abstract

The NFDI4DataScience (NFDI4DS) project aims to enhance the accessibility and interoperability of research data within Data Science (DS) and Artificial Intelligence (AI) by connecting digital artifacts and ensuring they adhere to FAIR (Findable, Accessible, Interoperable, and Reusable) principles. To this end, this poster introduces the NFDI4DS Ontology, which describes resources in DS and AI and models the structure of the NFDI4DS consortium. Built upon the NFDICore ontology and mapped to the Basic Formal Ontology (BFO), this ontology serves as the foundation for the NFDI4DS knowledge graph currently under development.

Keywords

knowledge representation

Cite

@article{arxiv.2408.08698,
  title  = {NFDI4DSO: Towards a BFO Compliant Ontology for Data Science},
  author = {Genet Asefa Gesese and Jörg Waitelonis and Zongxiong Chen and Sonja Schimmler and Harald Sack},
  journal= {arXiv preprint arXiv:2408.08698},
  year   = {2024}
}

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