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Ontologies4Cat: investigating the landscape of ontologies for catalysis research data management
As scientific digitization advances it is imperative ensuring data is Findable, Accessible, Interoperable, and Reusable (FAIR) for machine-processable data. Ontologies play a vital role in enhancing data FAIRness by explicitly representing knowledge in a machine-understandable format. Research data...
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Published in: | Journal of cheminformatics 2024-02, Vol.16 (1), p.16-16, Article 16 |
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creator | Behr, Alexander S. Borgelt, Hendrik Kockmann, Norbert |
description | As scientific digitization advances it is imperative ensuring data is Findable, Accessible, Interoperable, and Reusable (FAIR) for machine-processable data. Ontologies play a vital role in enhancing data FAIRness by explicitly representing knowledge in a machine-understandable format. Research data in catalysis research often exhibits complexity and diversity, necessitating a respectively broad collection of ontologies. While ontology portals such as EBI OLS and BioPortal aid in ontology discovery, they lack deep classification, while quality metrics for ontology reusability and domains are absent for the domain of catalysis research. Thus, this work provides an approach for systematic collection of ontology metadata with focus on the catalysis research data value chain. By classifying ontologies by subdomains of catalysis research, the approach is offering efficient comparison across ontologies. Furthermore, a workflow and codebase is presented, facilitating representation of the metadata on GitHub. Finally, a method is presented to automatically map the classes contained in the ontologies of the metadata collection against each other, providing further insights on relatedness of the ontologies listed. The presented methodology is designed for its reusability, enabling its adaptation to other ontology collections or domains of knowledge. The ontology metadata taken up for this work and the code developed and described in this work are available in a GitHub repository at:
https://github.com/nfdi4cat/Ontology-Overview-of-NFDI4Cat
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doi_str_mv | 10.1186/s13321-024-00807-2 |
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https://github.com/nfdi4cat/Ontology-Overview-of-NFDI4Cat
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https://github.com/nfdi4cat/Ontology-Overview-of-NFDI4Cat
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Finally, a method is presented to automatically map the classes contained in the ontologies of the metadata collection against each other, providing further insights on relatedness of the ontologies listed. The presented methodology is designed for its reusability, enabling its adaptation to other ontology collections or domains of knowledge. The ontology metadata taken up for this work and the code developed and described in this work are available in a GitHub repository at:
https://github.com/nfdi4cat/Ontology-Overview-of-NFDI4Cat
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subjects | Analysis Catalysis Chemistry Chemistry and Materials Science Classification Computational Biology/Bioinformatics Computer Applications in Chemistry Data management Documentation and Information in Chemistry Information management Investigations Knowledge representation Metadata Ontology Ontology classification Ontology collection Research data management Semantic web Theoretical and Computational Chemistry Workflow |
title | Ontologies4Cat: investigating the landscape of ontologies for catalysis research data management |
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