M Talebpour KEOD 2017.pdf (175.86 kB)
The role of community and social metrics in ontology evaluation: An interview study of ontology reuse
conference contribution
posted on 2018-12-14, 11:25 authored by Marzieh Talebpour, Martin SykoraMartin Sykora, Tom JacksonTom JacksonFinding a "good" or the "right" ontology for reuse is an ongoing challenge in the field of ontology engineering, where the main aim is to share and reuse existing semantics. This paper reports on a qualitative study with interviews of ontologists and knowledge engineers in different domains, ranging from biomedical field to manufacturing industry, and investigates the challenges they face while searching, evaluating, and selecting an ontology for reuse. Analysis of the interviews reveals diverse sets of quality metrics that are used when evaluating the quality of an ontology. While some of the metrics have already been mentioned in the literature, the findings from our study identify new sets of quality metrics such as community and social related metrics. We believe that this work represents a noteworthy contribution to the field of ontology engineering, with the hope that the research community can further draw on these initial findings in developing relevant quality metrics and ontology search and selection.
History
School
- Business and Economics
Department
- Business
Published in
IC3K 2017 - Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge ManagementVolume
2Pages
119 - 127Citation
TALEBPOUR, M., SYKORA, M.D. and JACKSON, T., 2017. The role of community and social metrics in ontology evaluation: An interview study of ontology reuse. IN: Aveiro, D., Dietz, J. and Filipe, J. (eds). Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2017), Funchal, Madeira, Portugal, 1-3 November 2017, Volume 2: KEOD, pp.119-127.Publisher
© SCITEPRESS – Science and Technology PublicationsVersion
- AM (Accepted Manuscript)
Publisher statement
This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/Publication date
2017Notes
This conference paper was published in Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, Volume 2 and the definitive published version is available at https://doi.org/10.5220/0006589201190127.ISBN
9789897582721Publisher version
Language
- en