Description of Ontology Metadata with NFDIcore

Ontologies play a central role in enabling sharing and reusing of knowledge on the Semantic Web. However, discovering suitable ontologies remains a major challenge, largely due to fragmented and insufficient metadata. Existing metadata schemas often suffer from limited scope, lack of harmonization, and poor maintainability, making it difficult to support their effective discovery, reuse, and reasoning.This work presents a novel approach to ontology metadata management, grounded in the newly released NFDIcore Ontology 3.0 [1]. The proposed metadata schema leverages NFDIcore’s semantic modeling capabilities to enhance interoperability and expressiveness. Aligned with the FAIR principles and the broader goals of the National Research Data Infrastructure (NFDI), the initiative aims to establish unified and queryable knowledge graphs that semantically describe ontologies across diverse research domains.A dedicated tool has been developed to automatically harvest ontologies from GitHub, extracting key structural and descriptive metadata such as versions, variants, domain coverage, and contributors. This metadata is formalized using NFDIcore and mapped to the Data Catalog Vocabulary (DCAT) [2], ensuring compatibility with existing standards. In addition, the organizational structures of ontology repositories are modeled, and their evolution over time is tracked to ensure transparent and up-to-date metadata.To address core challenges such as findability, inconsistent metadata structures, inadequate versioning, and ambiguous URI usage, current solutions are critically examined, and the proposed approach is introduced as a comprehensive alternative. Future work includes enriching the metadata with both quantitative and qualitative insights, including ontology size, conceptual granularity, and specific domains of application.The approach contributes to the development of semantically rich and interoperable infrastructure that supports ontology discovery, integration, and reuse, both within the NFDI ecosystem and beyond.References:[1] Bruns, O., Tietz, T., Waitelonis, J., Posthumus, E., & Sack, H. (2024). NFDIcore 2.0: A BFO-Compliant Ontology for Multi-Domain Research Infrastructures. arXiv preprint arXiv:2410.01821.[2] W. W. W. Consortium et al. Data catalog vocabulary (dcat). 2014

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-08-29
DOI
https://doi.org/10.5281/zenodo.17158442
Primary Topic
Geochemistry and Geologic Mapping
Type
article
Field-Weighted Citation Impact
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article

Description of Ontology Metadata with NFDIcore

Zenodo (CERN European Organization for Nuclear Research)
Geochemistry and Geologic Mapping
article

Description of Ontology Metadata with NFDIcore

article en

Abstract

Ontologies play a central role in enabling sharing and reusing of knowledge on the Semantic Web. However, discovering suitable ontologies remains a major challenge, largely due to fragmented and insufficient metadata. Existing metadata schemas often suffer from limited scope, lack of harmonization, and poor maintainability, making it difficult to support their effective discovery, reuse, and reasoning.This work presents a novel approach to ontology metadata management, grounded in the newly released NFDIcore Ontology 3.0 [1]. The proposed metadata schema leverages NFDIcore’s semantic modeling capabilities to enhance interoperability and expressiveness. Aligned with the FAIR principles and the broader goals of the National Research Data Infrastructure (NFDI), the initiative aims to establish unified and queryable knowledge graphs that semantically describe ontologies across diverse research domains.A dedicated tool has been developed to automatically harvest ontologies from GitHub, extracting key structural and descriptive metadata such as versions, variants, domain coverage, and contributors. This metadata is formalized using NFDIcore and mapped to the Data Catalog Vocabulary (DCAT) [2], ensuring compatibility with existing standards. In addition, the organizational structures of ontology repositories are modeled, and their evolution over time is tracked to ensure transparent and up-to-date metadata.To address core challenges such as findability, inconsistent metadata structures, inadequate versioning, and ambiguous URI usage, current solutions are critically examined, and the proposed approach is introduced as a comprehensive alternative. Future work includes enriching the metadata with both quantitative and qualitative insights, including ontology size, conceptual granularity, and specific domains of application.The approach contributes to the development of semantically rich and interoperable infrastructure that supports ontology discovery, integration, and reuse, both within the NFDI ecosystem and beyond.References:[1] Bruns, O., Tietz, T., Waitelonis, J., Posthumus, E., & Sack, H. (2024). NFDIcore 2.0: A BFO-Compliant Ontology for Multi-Domain Research Infrastructures. arXiv preprint arXiv:2410.01821.[2] W. W. W. Consortium et al. Data catalog vocabulary (dcat). 2014

Zenodo (CERN European Organization for Nuclear Research)
FIZ Karlsruhe – Leibniz Institute for Information Infrastructure (DE)
Industry, innovation and infrastructure
Openalex Percentile: Top 34%
Geochemistry and Geologic Mapping
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