Ontology Verification Using Contexts

Ontologies have become the de-facto modeling tool of choice, used in a variety of applications and prominently in the Semantic Web. Their design and maintenance, nevertheless, have been and still are a daunting task. As a result, ontologies quickly become underspecified. Therefore, if ontologies do not evolve, the semantic infrastructure of the information system can no longer support the changing needs of the organization. In this work we provide a model and a set of algorithms to semi-automatically support relationship evolution in an ontology using contexts. We propose to use (machine-generated) contexts as a mechanism for quantifying relationships among concepts. To do so we compare the contexts that are associated with the ontology constructs. We believe that such a solution will provide significant assistance in supporting ontology design and evolution. The main contribution of this work is twofold. On a conceptual level, we introduce an ontology verification model, a quantified model for automatically assessing the validity of relationships in an ontology. On an algorithmic level, we provide a mapping of several ontology operators for defining relationships into context relationships. We motivate our work with examples from the field of eGovernment applications and support our model with an empirical analysis, using real-world traces of RSS and Reuters.