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Evolution of computational ontologies: Assessing development processes using metrics
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
2023 (English)In: Knowledge Discovery, Knowledge Engineering and Knowledge Management: 14th International Joint Conference, IC3K 2022, Valletta, Malta, October 24–26, 2022, Revised Selected Papers / [ed] F. Coenen, A. Fred, D. Aveiro, J. Dietz, J. Bernardino, E. Masciari, & J. Filipe, Cham: Springer, 2023, p. 217-238Conference paper, Published paper (Refereed)
Abstract [en]

Ontologies serve as a bridge between humans and computers. They encode domain knowledge to connect federated data sources or infer tacit knowledge. While the technology used in ontologies is widely adopted and can be considered mature, much has still to be learned about their evolution and development, as understanding ontology evolution could help ensure better quality control and provide knowledge engineers with helpful modeling and selection guidelines. This paper examines the evolution of computational ontologies using ontology metrics. The authors hypothesize that ontologies follow a similar development pattern. This assumption is broken down into five hypotheses and tested against historical metric data from 69 dormant ontologies and 7,053 versions. The research proved that the development processes of ontologies are highly diverse. While a slight majority of ontologies confirm some of the hypotheses, accepting them as a general rule is not possible. Further, the data revealed that most ontologies have disruptive change events for most measured attributes. These disruptive events are examined regarding their occurrences, combinations, and sizes. 

Place, publisher, year, edition, pages
Cham: Springer, 2023. p. 217-238
Series
Communications in Computer and Information Science, ISSN 1865-0929, E-ISSN 1865-0937 ; 1842
Keywords [en]
NEOntometrics, Ontology evaluation, Ontology evolution, Ontology metrics, Owl, Rdf, Domain Knowledge, Quality control, Resource Description Framework (RDF), Uncertainty analysis, Computational ontology, Development process, Neontometric, Ontology evaluations, Ontology's, Ontology
National Category
Information Systems
Identifiers
URN: urn:nbn:se:hj:diva-63372DOI: 10.1007/978-3-031-43471-6_10Scopus ID: 2-s2.0-85174322353ISBN: 9783031434709 (print)ISBN: 9783031434716 (electronic)OAI: oai:DiVA.org:hj-63372DiVA, id: diva2:1828254
Conference
14th International Joint Conference, IC3K 2022, Valletta, Malta, October 24–26, 2022
Available from: 2024-01-16 Created: 2024-01-16 Last updated: 2024-01-16Bibliographically approved

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Sandkuhl, Kurt

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