The OWL Web Ontology Language is a new formal language for representing ontologies in the Semantic Web. OWL has features from several families of representation languages, including primarily Description Logics and frames. OWL also shares many characteristics with RDF, the W3C base of the Semantic Web. In this paper we discuss how the philosophy and features of OWL can be traced back to these older formalisms, with modifications driven by several other constraints on OWL. Several interesting problems...

XML is the W3C standard document format for writing and exchanging information on the Web. RDF is the W3C standard model for describing the semantics and reasoning about information on the Web. Unfortunately, RDF and XML---although very close to each other---are based on two different paradigms. We argue that in order to lead the Semantic Web to its full potential, the syntax and the semantics of information needs to work together. To this end, we develop a model theory for the XML XQuery 1.0 and XPath 2.0 Data Model, which provides a unified model for both XML and RDF. This unified model can serve as the basis for Web applications that deal with both data and semantics. We illustrate the use of this model on a concrete information integration scenario. Our approach enables each side of the fence to benefit from the other, notably, we show how the RDF world can take advantage of XML query languages, and how the XML world can take advantage of the reasoning capabilities available for RDF.

The Sematic Web is vitally dependant on a formal meaning for the constructs of its languages. For Semantic Web languages to work well together their formal meanings must employ a common view (or thesis) of representation, otherwise it will not be possible to reconcile documents written in different languages. The thesis of representation underlying RDF and RDFS is particularly troublesome in this regard, as it has several unusual aspects, both semantic and syntactic. A more-standard thesis of representation would result in the ability to reuse existing results and tools in the Semantic Web.

In has been argued that ontologies play a key role in multiagent communication because they provide and define a shared vocabulary to be used in the course of communication. In real-life scenarios, however, the situation where two agents completely share a vocabulary is rather an exception. More often, each agent uses its own vocabulary specified in a private ontology that is not known by other agents. In this paper we propose a solution to this problem for the situation, where agents share at least parts of their vocabulary. We argue that the assumption of a partially shared vocabulary is valid and sketch an approach for re-formulating terms from the private part of an agent's ontology into a shared part thus enabling other agents to understand them. We further describe how the approach can be implemented using existing technology and proof the correctness of the re-formulation with respect to the semantics of the ontology-language DAML+OIL.

XML is the W3C standard document format for writing and exchanging information on the Web. RDF is the W3C standard model for describing the semantics and reasoning about information on the Web. Unfortunately, RDF and XML -- although very close to each other -- are based on two different paradigms. We argue that in order to lead the Semantic Web to its full potential, the syntax and the semantics of information need to work together. To this end, we develop a model theory for the XML XQuery 1.0 and XPath 2.0 Data Model, which provides a unified model for both XML and RDF. This unified model can serve as the basis for Web applications that deal with both data and semantics. We illustrate the use of this model on a concrete information integration scenario. Our approach enables each side of the fence to benefit from the other, notably, we show how the RDF world can take advantage of XML Schema description and XML query languages, and how the XML world can take advantage of the reasoning capabilities available for RDF. Our approach can also serve as a foundation for the next layer of the Semantic Web, the ontology layer, and we present a layering of an ontology language on top of our approach.

This article discusses how artificial intelligence (AI) planning techniques can be used to enable automatic composition of Web Services. Particulary, the paper discusses how standard Web Service descriptions can be annotated and converted into proper formats like PDDL to enable reasoning with modern AI planning tools. 1

Recent investigations have uncovered some problems in the relationship between daml+oil and the new rdf model theory. There are several ways of remedying these problems, resulting in greater or lesser compatability with rdf. One possible remedy is to diverge from the rdf philosophy only on statements about descriptions, resulting in a complex web ontology language containing a description logic and that is compatible with rdf. Another possible remedy is to remain compatible with rdf only on statements about individuals, resulting in a semantic web ontology language that is very close to standard description logics, but that is not fully compatible with rdf.

Abstract. Intelligent text information retrieval systems need the capability to deal with the semantics of the content of their text bases. In order to satisfy this requisite it is necessary to extract semantic information from the documents and to be able to make inferences about it. A methodology to semi-automatically transform a traditional web IR system into a semantic aware one is proposed. The methodology is composed by three major steps: construction of an appropriate semantic ontology; text enrichment with semantic information; and construction of the inference engine. In order to create an adequate ontology, natural language processing techniques are applied, such as, partial parsers and lexical information (WordNet). Documents are enriched with semantic information using the output of the partial parsers and the obtained ontology. Finally, an inference engine based on a declarative programming language – Prolog – is used as the basis for the reasoning process. An application of this methodology to the legal web information retrieval system of the Portuguese Attorney General’s Office is described. 1

It is widely accepted that the Semantic Web will be based on machine-readable metadata describing the content of resources. These descriptions are designed to enable intelligent agents to locate and filter relevant information with a higher level of accuracy. The Resource Description Framework (RDF) has been developed as universal language for encoding content-related metadata and recently a number of query languages have been proposed to extract information from metadata models.

ed terminological reasoning in order to facilitate the instance reasoning we also use problems included in the first three categories of problems. Up to now we check our implementation with respect to satifiability check with and without terminological axioms presented, TBox classification in both cases - realistic ontologies and generated ones. The present results show that our implementation is correct with respect to these reasoning tasks. The efficiency is still under the performance of the state-of-the-art implementation, as far as, BOR satisfies the time requirement only the for the first three problems in each group. Thus in our further work within the project we will target on integration, evaluation of the other reasoning services and optimizatoin of the performance. The BOR reasoner is available for downlaod at http://www.ontotext.com/bor together with more instructions on its installation, tests, and usage. 4 References