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Debunking the Stereotypical Ontology Development Process
Rostock University, Rostock, Germany.
Jönköping University, School of Engineering, JTH, Department of Computer Science and Informatics. Rostock University, Rostock, Germany.ORCID iD: 0000-0002-7431-8412
2022 (English)In: Proceedings of the 14th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - KEOD, 82-91, 2022 , Valletta, Malta, SciTePress, 2022, p. 82-91Conference paper, Published paper (Refereed)
Abstract [en]

Ontologies facilitate meaning between human and computational actors. On the one hand, the underlying technology can be considered mature. It has a standardized language, established tools for editing and sharing, and broad adoption in practice and research. On the other hand, we still know little about how these artifacts evolve over their lifetime, even though knowledge of the development process could influence quality control. It would enable us to give knowledge engineers better modeling or selection guidelines. This paper examines the evolution of computational ontologies using ontology metrics. First, we gathered hypotheses on the ontology development process. We assume that groups of ontologies follow a similar development pattern and that a stereotypical development process exists. Afterward, these hypotheses are tested against historical metric data from 7053 versions from 69 dormant ontologies. We will show that ontology development processes are highly heterogeneous. While the made hypotheses are partly true for a slight majority of ontologies, concluding the bigger picture of ontology development down to the individual ontologies is mostly not possible. 

Place, publisher, year, edition, pages
SciTePress, 2022. p. 82-91
Keywords [en]
NEOntometrics, Ontology Evaluation, Ontology Evolution, Ontology Metrics, OWL, RDF, Knowledge engineering, Knowledge management, Quality control, Resource Description Framework (RDF), Computational ontology, Development process, Neontometric, Ontology development, Ontology evaluations, Ontology's, Ontology
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:hj:diva-59488DOI: /10.5220/0011573600003335Scopus ID: 2-s2.0-85146197774ISBN: 9789897586149 (print)OAI: oai:DiVA.org:hj-59488DiVA, id: diva2:1740241
Conference
14th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - KEOD, 82-91, 2022 , Valletta, Malta
Available from: 2023-02-28 Created: 2023-02-28 Last updated: 2023-02-28Bibliographically approved

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Sandkuhl, Kurt

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