Contributing evidence to data-driven ontology evaluation workflow ontologies perspective

Hlomani Hlomani, Deborah A. Stacey

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

Ontologies have established themselves as the single most important semantic web technology. They have attracted widespread interest from both academic and industrial domains. This has led to an increase in ontologies created. It has become apparent that more than one ontology may model the same domain yet they can be very different. The question then is, how do you determine which ontology best fits your purposes? This paper endeavours to answer this question by reviewing relevant literature and instantiating the data-driven ontology evaluation methodology in the context of workflow ontologies. This evaluation methodology is then evaluated through statistical means particularly the Kruskal-Wallis test and further post hoc testing using the Mann-Whiteny U test.

Original languageEnglish
Title of host publicationIC3K 2013; KEOD 2013 - 5th International Conference on Knowledge Engineering and Ontology Development, Proceedings
Pages207-213
Number of pages7
Publication statusPublished - Nov 21 2013
Event5th International Conference on Knowledge Engineering and Ontology Development, KEOD 2013 - Vilamoura, Algarve, Portugal
Duration: Sep 19 2013Sep 22 2013

Other

Other5th International Conference on Knowledge Engineering and Ontology Development, KEOD 2013
CountryPortugal
CityVilamoura, Algarve
Period9/19/139/22/13

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All Science Journal Classification (ASJC) codes

  • Software

Cite this

Hlomani, H., & Stacey, D. A. (2013). Contributing evidence to data-driven ontology evaluation workflow ontologies perspective. In IC3K 2013; KEOD 2013 - 5th International Conference on Knowledge Engineering and Ontology Development, Proceedings (pp. 207-213)