Abstract:Recently, domain specific ontology development has been driven by research on the Semantic Web. Ontologies have been suggested for use in many application areas targeted by the Semantic Web, such as dynamic web service composition and general web service matching. Fundamental characteristics of these ontologies must be determined in order to effectively make use of them: for example, Sirin, Hendler and Parsia have suggested that determining fundamental characteristics of ontologies is important for dynamic web service composition. Our research examines cohesion metrics for ontologies. The cohesion metrics examine the fundamental quality of cohesion as it relates to ontologies.

No abstract

Many application areas today make use of ontologies. With the advent of semantic Web technologies, ontology based systems have become widespread. Developing an ontology is part of the necessary early development of an ontology‐based system. Since the validity and quality of the ontology data directly affects the validity and quality of the system using the ontology, evolution of the ontology data directly affects the evolution and/or maintenance of the ontology‐based systems that depend on and employ the ontology data. Our research examines the quality, completeness, and stability of ontology data as ontologies evolve. We propose a metrics suite, based on standard software quality concepts, to measure the complexity and cohesion of ontology data. First we theoretically validate our metrics. Then we examine empirically whether our metrics determine ontology data quality, by comparing them to human evaluator ratings. We conclude that several of our metrics successfully determine ontology complexity or cohesion. Finally, we examine, over evolving ontology data, whether our metrics determine ontology completeness and stability. We determine that various metrics reflect different kinds of changes. Our experiments indicate our metrics' measure ontology stability and completeness; however, interpretation of specific metrics values and the interaction of different metrics requires further study. Copyright © 2007 John Wiley & Sons, Ltd.

No abstract