Abstract. The Web Service Modeling Language (WSML) is a language for the specification of different aspects of Semantic Web Services. It provides a formal language for the Web Service Modeling Ontology WSMO which is based on well-known logical formalisms, specifying one coherent language framework for the semantic description of Web Services, starting from the intersection of Datalog and the Description Logic SHIQ. This core language is extended in the directions of Description Logics and Logic Programming in a principled manner with strict layering. WSML distinguishes between conceptual and logical modeling in order to support users who are not familiar with formal logic, while not restricting the expressive power of the language for the expert user. IRIs play a central role in WSML as identifiers. Furthermore, WSML defines XML and RDF serializations for inter-operation over the Semantic Web.

Ontology mediation is a broad field of research which is concerned with determining and overcoming differences between ontologies in order to allow the reuse of such ontologies, and the data annotated using these ontologies, throughout different heterogeneous applications.Ontology mediation can be subdivided into three areas: ontology mapping, which is mostly concerned with the representation of correspondences between ontologies; ontology alignment, which is concerned with the (semi-)automatic discovery of correspondences between ontologies; and ontology merging, which is concerned with creating a single new ontology, based on a number of source ontologies. This chapter reviews the work which has been done in the three mentioned areas and proposes an integrated approach to ontology mediation in the area of knowledge management. A language is developed for the representation of correspondences between ontologies. An algorithm, which generalizes current state-of-the-art alignment algorithms, is developed for the (semi-)automated discovery of such mappings. A tool is presented for browsing and editing ontology mappings. An ontology mapping can be used for a variety of different tasks, such as transforming data between different representations and querying different heterogeneous knowledge bases.

Abstract. Hierarchical classifications, thesauri, and informal taxonomies are likely the most valuable input for creating, at reasonable cost, non-toy ontologies in many domains. They contain, readily available, a wealth of category definitions plus a hierarchy, and they reflect some degree of community consensus. However, their transformation into useful ontologies is not as straightforward as it appears. In this paper, we show that (1) it often depends on the context of usage whether an informal hierarchical categorization schema is a classification, a thesaurus, or a taxonomy, and (2) present a novel methodology for automatically deriving consistent RDF-S and OWL ontologies from such schemas. Finally, we (3) demonstrate the usefulness of this approach by transforming the two e-business categorization standards eCl@ss and UNSPSC into ontologies that overcome the limitations of earlier prototypes. Our approach allows for the script-based creation of meaningful ontology classes for a particular context while preserving the original hierarchy, even if the latter is not a real subsumption hierarchy in this particular context. Human intervention in the transformation is limited to checking some conceptual properties and identifying frequent anomalies, and the only input required is an informal categorization plus a notion of the target context. In particular, the approach does not require instance data, as ontology learning approaches would usually do.

Recently, there has been a lot of interest in the integration of Description Logics and rules on the Semantic Web. We define guarded hybrid knowledge bases (or g-hybrid knowledge bases) as knowledge bases that consist of a Description Logic knowledge base and a guarded logic program, similar to the DL+log knowledge bases from (Rosati 2006). G-hybrid knowledge bases enable an integration of Description Logics and Logic Programming where, unlike in other approaches, variables in the rules of a guarded program do not need to appear in positive non-DL atoms of the body, i.e. DL atoms can act as guards as well. Decidability of satisfiability checking of g-hybrid knowledge bases is shown for the particular DL DLRO −{≤} , which is close to OWL DL, by a reduction to guarded programs under the open answer set semantics. Moreover, we show 2-EXPTIME-completeness for satisfiability checking of such g-hybrid knowledge bases. Finally, we discuss advantages and disadvantages of our approach compared with DL+log knowledge bases. AbstractRecently, there has been a lot of interest in the integration of Description Logics and rules on the Semantic Web. We define guarded hybrid knowledge bases (or g-hybrid knowledge bases) as knowledge bases that consist of a Description Logic knowledge base and a guarded logic program, similar to the DL+log knowledge bases from (?). G-hybrid knowledge bases enable an integration of Description Logics and Logic Programming where, unlike in other approaches, variables in the rules of a guarded program do not need to appear in positive non-DL atoms of the body, i.e. DL atoms can act as guards as well. Decidability of satisfiability checking of g-hybrid knowledge bases is shown for the particular DL DLRO −{≤} , which is close to OWL DL, by a reduction to guarded programs under the open answer set semantics. Moreover, we show 2-EXPTIME-completeness for satisfiability checking of such g-hybrid knowledge bases. Finally, we discuss advantages and disadvantages of our approach compared with DL+log knowledge bases.

Abstract. In the ongoing discussion about combining rules and Ontologies on the Semantic Web a recurring issue is how to combine first-order classical logic with nonmonotonic rule languages. Whereas several modular approaches to define a combined semantics for such hybrid knowledge bases focus mainly on decidability issues, we tackle the matter from a more general point of view. In this paper we show how Quantified Equilibrium Logic (QEL) can function as a unified framework which embraces classical logic as well as disjunctive logic programs under the (open) answer set semantics. In the proposed variant of QEL we relax the unique names assumption, which was present in earlier versions of QEL. Moreover, we show that this framework elegantly captures the existing modular approaches for hybrid knowledge bases in a unified way.