Semantic Web Service, one of the most significant research areas within the Semantic Web vision, has attracted increasing attention from both the research community and industry. The Web Service Modelling Ontology (WSMO) has been proposed as an enabling framework for the total/partial automation of the tasks (e.g., discovery, selection, composition, mediation, execution, monitoring and etc.) involved in both intra-and inter-enterprise integration of Web Services. To support the standardisation and tool support of WSMO, a formal model of the language is highly desirable. As several variants of WSMO have been proposed by the WSMO community, which are still under development, the syntax and semantics of WSMO should be formally defined to facilitate easy reuse and future development. In this paper, we present a formal Object-Z formal model of WSMO, where different aspects of the language have been precisely defined within one unified framework. This model not only provides a formal unambiguous model which can be used to develop tools and facilitate future development, but as demonstrated in this paper, can be used to identify and eliminate errors present in existing documentation.

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Abstract. This paper presents a method for encoding OWL-S atomic processes by means of SWRL rules and composing them using a backward search planning algorithm. A description of the preliminary prototype implementation is also presented.

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Abstract. The base of Semantic Web specifications is Resource Description Framework (RDF) as a standard for expressing metadata. RDF has a simple object model, allowing for easy design of knowledge bases. This implies that the size of knowledge bases can dramatically increase; therefore, it is necessary to take into account both scalability and space consumption when storing such bases. Some theoretical results related to blank node semantics can be exploited in order to design techniques that optimize, among others, space requirements in storing RDF descriptions. We present an algorithm, called REDD, that exploits these theoretical results and optimizes the space used by a RDF description. MotivationThe realization of the Semantic Web (SW) vision [1] needs ontologies for generating or interpreting (semantic) metadata for resources. It is fundamental to have ontology creation and integration steps in order to share structural knowledge between ontology designers and users. Ontologies are to be expressed in RDF according to SW specifications, using languages such as RDFS 1 and OWL. 2 It is important to note that both RDFS and OWL ontologies can be expressed as RDF graphs, so that ontologies can be treated exactly as other RDF models. In RDF design, the least power principle was applied: data structures are to be kept as simple as possible. This imposes to have very simple basic components, that are URIs 3 , blank nodes and statements (or triples). These design decisions have the drawback that RDF descriptions tend to grow fast as the complexity of the knowledge they represent increases. This observation encourages SW research to investigate toward the most effective storage solutions for RDF knowledge bases, in order to minimize required space. Intuitively, the lesser the number of triples a software (say, a query engine) has to examine, the faster it will process them.