An extension to the data-driven ontology evaluation

Within the semantic web domain, ontologies are an important artifact. Such words as "pivotal" have been associated with the role they play on the semantic web. The role they play on the semantic web as well as their potential for reuse and the proliferation of ontologies in existence have...

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Bibliographic Details
Published inProceedings of the 2014 IEEE 15th International Conference on Information Reuse and Integration (IEEE IRI 2014) pp. 845 - 849
Main Authors Hlomani, Hlomani, Stacey, Deborah
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2014
Subjects
Approximation methods
Business
Context
data-driven ontology evaluation
Measurement
metrics
Ontologies
Ontology
ontology evaluation
Semantic Web
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Summary:Within the semantic web domain, ontologies are an important artifact. Such words as "pivotal" have been associated with the role they play on the semantic web. The role they play on the semantic web as well as their potential for reuse and the proliferation of ontologies in existence have heightened the need for their evaluation. They have been seen as approximate representations of the domain, thus their evaluation concerns itself with the degree of their approximation. This research deemed domain knowledge on which data-driven ontology evaluation is based to be dynamic. This is contrary to the underlying assumptions of current research in data-driven ontology evaluation. The paper hence proposes a multidimensional view to data-driven ontology evaluation that accounts for bias in the valuation of ontologies. The direct contribution to the body of knowledge is a theoretical framework that exposes these biases.
DOI:10.1109/IRI.2014.7051978