Abstract
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.
Original language | English |
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Title of host publication | Proceedings of the 2014 IEEE 15th International Conference on Information Reuse and Integration, IEEE IRI 2014 |
Editors | Elisa Bertino, Bhavani Thuraisingham, Ling Liu, James Joshi |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 845-849 |
Number of pages | 5 |
ISBN (Electronic) | 9781479958801 |
DOIs | |
Publication status | Published - Feb 27 2014 |
Event | 15th IEEE International Conference on Information Reuse and Integration, IEEE IRI 2014 - San Francisco, United States Duration: Aug 13 2014 → Aug 15 2014 |
Other
Other | 15th IEEE International Conference on Information Reuse and Integration, IEEE IRI 2014 |
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Country/Territory | United States |
City | San Francisco |
Period | 8/13/14 → 8/15/14 |
All Science Journal Classification (ASJC) codes
- Information Systems