Completing and Debugging Ontologies: state of the art and challenges

As semantically-enabled applications require high-quality ontologies, developing and maintaining ontologies that are as correct and complete as possible is an important although difficult task in ontology engineering. A key step is ontology debugging and completion. In general, there are two steps: detecting defects and repairing defects. In this paper we discuss the state of the art regarding the repairing step. We do this by formalizing the repairing step as an abduction problem and situating the state of the art with respect to this framework. We show that there are still many open research problems and show opportunities for further work and advancing the field.Comment: 56 page

Recursive Online Enumeration of All Minimal Unsatisfiable Subsets

In various areas of computer science, we deal with a set of constraints to be satisfied. If the constraints cannot be satisfied simultaneously, it is desirable to identify the core problems among them. Such cores are called minimal unsatisfiable subsets (MUSes). The more MUSes are identified, the more information about the conflicts among the constraints is obtained. However, a full enumeration of all MUSes is in general intractable due to the large number (even exponential) of possible conflicts. Moreover, to identify MUSes algorithms must test sets of constraints for their simultaneous satisfiabilty. The type of the test depends on the application domains. The complexity of tests can be extremely high especially for domains like temporal logics, model checking, or SMT. In this paper, we propose a recursive algorithm that identifies MUSes in an online manner (i.e., one by one) and can be terminated at any time. The key feature of our algorithm is that it minimizes the number of satisfiability tests and thus speeds up the computation. The algorithm is applicable to an arbitrary constraint domain and its effectiveness demonstrates itself especially in domains with expensive satisfiability checks. We benchmark our algorithm against state of the art algorithm on Boolean and SMT constraint domains and demonstrate that our algorithm really requires less satisfiability tests and consequently finds more MUSes in given time limits

Debugging and repair of description logic ontologies.

Thesis (M.Sc.)-University of KwaZulu-Natal, Westville, 2010.In logic-based Knowledge Representation and Reasoning (KRR), ontologies are used to represent knowledge about a particular domain of interest in a precise way. The building blocks of ontologies include concepts, relations and objects. Those can be combined to form logical sentences which explicitly describe the domain. With this explicit knowledge one can perform reasoning to derive knowledge that is implicit in the ontology. Description Logics (DLs) are a group of knowledge representation languages with such capabilities that are suitable to represent ontologies. The process of building ontologies has been greatly simpli ed with the advent of graphical ontology editors such as SWOOP, Prote ge and OntoStudio. The result of this is that there are a growing number of ontology engineers attempting to build and develop ontologies. It is frequently the case that errors are introduced while constructing the ontology resulting in undesirable pieces of implicit knowledge that follows from the ontology. As such there is a need to extend current ontology editors with tool support to aid these ontology engineers in correctly designing and debugging their ontologies. Errors such as unsatis able concepts and inconsistent ontologies frequently occur during ontology construction. Ontology Debugging and Repair is concerned with helping the ontology developer to eliminate these errors from the ontology. Much emphasis, in current tools, has been placed on giving explanations as to why these errors occur in the ontology. Less emphasis has been placed on using this information to suggest e cient ways to eliminate the errors. Furthermore, these tools focus mainly on the errors of unsatis able concepts and inconsistent ontologies. In this dissertation we ll an important gap in the area by contributing an alternative approach to ontology debugging and repair for the more general error of a list of unwanted sentences. Errors such as unsatis able concepts and inconsistent ontologies can be represented as unwanted sentences in the ontology. Our approach not only considers the explanation of the unwanted sentences but also the identi cation of repair strategies to eliminate these unwanted sentences from the ontology