No abstract

No abstract

No abstract

Abstract. Service interface description languages such as WSDL, and related standards, are evolving rapidly to provide a foundation for interoperation between Web services. At the same time, Semantic Web service technologies, such as the Ontology Web Language for Services (OWL-S), are developing the means by which services can be given richer semantic specifications. Richer semantics can enable fuller, more flexible automation of service provision and use, and support the construction of more powerful tools and methodologies. Both sets of technologies can benefit from complementary uses and crossfertilization of ideas. This paper shows how to use OWL-S in conjunction with Web service standards, and explains and illustrates the value added by the semantics expressed in OWL-S.

Automated composition of Web Services can be achieved by using AI planning techniques. Hierarchical Task Network (HTN) planning is especially well-suited for this task. In this paper, we describe how HTN planning system SHOP2 can be used with OWL-S Web Service descriptions. We provide a sound and complete algorithm to translate OWL-S service descriptions to a SHOP2 domain. We prove the correctness of the algorithm by showing the correspondence to the situation calculus semantics of OWL-S. We implemented a system that plans over sets of OWL-S descriptions using SHOP2 and then executes the resulting plans over the Web. The system is also capable of executing information-providing Web Services during the planning process. We discuss the challenges and difficulties of using planning in the information-rich and human-oriented context of Web Services.

No abstract

Abstract. Finding the justifications of an entailment (that is, all the minimal set of axioms sufficient to produce an entailment) has emerged as a key inference service for the Web Ontology Language (OWL). Justifications are essential for debugging unsatisfiable classes and contradictions. The availability of justifications as explanations of entailments improves the understandability of large and complex ontologies. In this paper, we present several algorithms for computing all the justifications of an entailment in an OWL-DL Ontology and show, by an empirical evaluation, that even a reasoner independent approach works well on real ontologies.

Abstract. In this paper, we investigate the problem of repairing unsatisfiable concepts in an OWL ontology in detail, keeping in mind the user perspective as much as possible. We focus on various aspects of the repair process -improving the explanation support to help the user understand the cause of error better, exploring various strategies to rank erroneous axioms (with motivating use cases for each strategy), automatically generating repair plans that can be customized easily, and suggesting appropriate axiom edits where possible to the user. Based on the techniques described, we present a preliminary version of an interactive ontology repair tool and demonstrate its applicability in practice.