Debugging Classical Ontologies Using Defeasible Reasoning Tools

Abstract

A successful application of ontologies relies on representing as much accurate and relevant domain knowledge as possible, while maintaining logical consistency. As the successful implementation of a real-world ontology is likely to contain many concepts and intricate relationships between the concepts, it is necessary to follow a methodology for debugging and refining the ontology. Many ontology debugging approaches have been developed to help the knowledge engineer pinpoint the cause of logical inconsistencies and rectify them in a strategic way. We show that existing debugging approaches can lead to unintuitive results, which may lead the knowledge engineer to opt for deleting potentially crucial and nuanced knowledge. We provide a methodological and design foundation for weakening faulty axioms in a strategic way using defeasible reasoning tools. Our methodology draws from Rodler’s interactive ontology debugging approach and extends this approach by creating a methodology to systematically find conflict resolution recommendations. Importantly, our goal is not to convert a classical ontology to a defeasible ontology. Rather, we use the definition of exceptionality of a concept, which is central to the semantics of defeasible description logics, and the associated algorithm to determine the extent of a concept’s exceptionality (their ranking); then, starting with the statements containing the most general concepts (the least exceptional concepts) weakened versions of the original statements are constructed; this is done until all inconsistencies have been resolved.

Towards counterfactual explanations for ontologies

“…The size of the search space is linked to the size of the ontology; the method would not execute in a reasonable time for a large ontology. Other explanation methods for ontologies only run the logical reasoner a few times ( [1,7]), whereas the CEO method calls it for every explored counterfactual. Hence, it is not yet adequate for debugging large ontologies.…”

“…Its goal is to ask the user for additional knowledge that can reduce the length of proofs and justifications. However, Coetzer and Britz [7] have shown that the debugging approach of OntoDebug can lead to unintuitive results. Despite all the efforts in the development of debugging tools, ontology authors still struggle to debug and repair their ontologies [31].…”