OMNIMOD: Automating Ontology Modularization for Digital Library Data Using CIDOC-CRM as Use Case
conference paper
This paper introduces OMNIMOD, a new method designed to modularize ontologies, RDF-based structures that organize knowledge within specialized domains. By simplifying complex information into manageable components, OMNIMOD enhances the analysis, understandability, and navigation of large ontological frame works while also extending its functionality to include the modularization of associated data records, known as instance data. The method has been developed based on theoretical insights gathered from Cognitive Load Theory (CLT) and has been successfully tested and applied to CIDOC-CRM (Conceptual Reference Model of the International Committee for Documentation), the ISO standard for describing data related to cultural her itage materials. The accompanying Python functions, developed for OMNIMOD and provided in the corpus of the text, empower readers to adapt and utilize OMNIMOD according to their specific needs.
TNO Identifier
1005173
ISSN
978-989-758-718-4
Source title
Proceedings of the 20th International Conference on Web Information Systems and Technologies
Pages
102-111
Files
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