Analysing Multiple Versions of an Ontology

Abstract

The detection of changes between OWL ontologies is an important service for ontology engineering. There are several approaches to this problem, both syntactic and semantic. A purely syntactic analysis of changes is insufficient to detect changes with logical effect, while the current state of the art in semantic diffing ignores logically ineffectual changes, which might be of great interest to the user. We develop an exhaustive categorisation of ineffectual changes, based on their justifications. In order to verify the applicability of our approach, we col- lected 88 OWL versions of the National Cancer Institute (NCI) Thesaurus (NCIt), and extracted all pairwise, consecutive diffs. We discovered a substantial number of ineffectual changes and, as a result, argue that the devised categorisation of changes is beneficial for ontology engineers. We devised and applied a method for performance impact analysis (culprit finding) based on the diff between on- tologies, and identified a number of culprits between two NCIt versions.


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