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. Discovery is a central reasoning task in service-oriented architectures, concerned with detecting Web services that are usable for solving a given request. This paper presents two extensions in continuation of previous works towards goal-based Web service discovery with sophisticated semantic matchmaking. At first, we distinguish goal templates as generic objective descriptions and goal instances that denote concrete requests as an instantiation of a goal template. Secondly, we formally describe requested and provided functionalities on the level of state transitions that denote executions of Web services, respectively solutions for goals. Upon this, we specify a two-phase discovery procedure along with semantic matchmaking techniques that allow to accurately determine the usability of a Web service. The techniques are defined in the Abstract State Space model that supports several languages for describing Web services.
Abstract:Reasoning with large amounts of data together with ontological knowledge is becoming a pertinent issue. In this chapter, we will give an overviewof wellknown ontology repositories, including native stores and database based stores, and highlight strengths and limitations of each store. We take Minerva as an example to analyze ontology storage in databases in depth, as well as to discuss efficient indexes for scaling up ontology repositories. We then discuss a scalable reasoning method for handling expressive ontologies, as well as summarize other similar approaches. We will subsequently delve into the details of one particular ontology language based on Description Logics called WSML-DL and show that reasoning with this language can be done by a transformation from WSML-DL to OWL DL and support all main DL-specific reasoning tasks. Finally, we illustrate reasoning and its relevance by showing a reasoning example in a practical business context by presenting the Semantic Business Process Repository (SBPR) for systemical management of semantic business process models. As part of this, we analyze the main requirements on a such a repository. We then compare different approaches for storage mechanisms for this purpose and show how a RDBMS in combination with the IRIS inference engine provides a suitable solution that deals well with the expressiveness of the query language and the required reasoning capabilities even for large amounts of instance data.
Abstract. An important open question in the semanticWeb is the precise relationship between the RDF(S) semantics and the semantics of standard knowledge representation formalisms such as logic programming and description logics. In this paper we address this issue by considering embeddings of RDF and RDFS in logic. Using these embeddings, combined with existing results about various fragments of logic, we establish several novel complexity results. The embeddings we consider show how techniques from deductive databases and description logics can be used for reasoning with RDF(S). Finally, we consider querying RDF graphs and establish the data complexity of conjunctive querying for the various RDF entailment regimes.
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