Constraint Generation and Reasoning in OWL

The majority of OWL ontologies in the emerging Semantic Web are constructed from properties that lack domain and range constraints. Constraints in OWL are different from the familiar uses in programming languages and databases, and are actually type assertions that are made about the individuals which are connected by the property. These assertions can add vital information to the model because they are assertions of type on the individuals involved, and they can also give information on how the defining property may be used.

Three different automated generation techniques are explored in this research: disjunction, least-common named subsumer, and vivification. Each algorithm is compared for the ability to generalize, and the performance impacts with respect to the reasoner. A large sample of ontologies from the Swoogle repository are used to compare real-world performance of these techniques.

Finally, using generated facts, a type of default reasoning, may conflict with future assertions to the knowledge base. While general default reasoning is non-monotonic and undecidable a novel approach is introduced to support efficient retraction of the default knowledge. Combined, these techniques enable a robust and efficient generation of domain and range constraints which will result in inference of additional facts and improved performance for a number of Semantic Web applications. Ph.D. Dissertation Defense