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Abstract

The global economy is rapidly becoming more and more knowledge intensive. Knowledge is now widely recognized as the fourth production factor, on an equal footing with the traditional production factors of labour, capital and materials. Managing knowledge is as important as the traditional management of labour, capital and materials. In this book, we have shown how Semantic Web technology can make an important contribution to knowledge management.

Source

Towards the semantic Web: ontology-driven knowledge management. Eds.: J. Davies, u.a

Theme

Semantic Web

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Abstract

This chapter discusses OIL and DAML1OIL, currently the most prominent ontology languages for the Semantic Web. The chapter starts by discussing the pyramid of languages that underlie the architecture of the Semantic Web (XML, RDF, RDFS). In section 2.2, we briefly describe XML, RDF and RDFS. We then discuss in more detail OIL and DAML1OIL, the first proposals for languages at the ontology layer of the semantic pyramid. For OIL (and to some extent DAML1OIL) we discuss the general design motivations (Section 2.3), describe the constructions in the language (Section 2.4), and the various syntactic forms of these languages (Section 2.5). Section 2.6 discusses the layered architecture of the language, section 2.7 briefly mentions the formal semantics, section 2.8 discusses the transition from OIL to DAML+OIL, and section 2.9 concludes with our experience with the language to date and future development in the context of the World Wide Web Consortium (W3C). This chapter is not intended to give full and formal definitions of either the syntax or the semantics of OIL or DAML1OIL. Such definitions are already available elsewhere: http://www.ontoknowledge.org/oil/ for OIL and http://www.w3.org/submission/2001/12/ for DAML1OIL.

Source

Towards the semantic Web: ontology-driven knowledge management. Eds.: J. Davies, u.a

Theme

Semantic Web

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Source

Towards the semantic Web: ontology-driven knowledge management. Eds.: J. Davies, u.a

Theme

Semantic Web

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Abstract

The resource description framework (RDF) is a W3C recommendation for the formulation of meta-data on the World Wide Web. RDF Schema (RDFS) extends this standard with the means to specify domain vocabulary and object structures. These techniques will enable the enrichment of the Web with machine-processable semantics, thus giving rise to what has been dubbed the Semantic Web. We have developed Sesame, an architecture for storage and querying of RDF and RDFS information. Sesame allows persistent storage of RDF data and schema information, and provides access methods to that information through export and querying modules. It features ways of caching information and offers support for concurrency control. This chapter is organized as follows: In Section 5.2 we discuss why a query language specifically tailored to RDF and RDFS is needed, over and above existing query languages such as XQuery. In Section 5.3 we look at Sesame's modular architecture in some detail. In Section 5.4 we give an overview of the SAIL API and a brief comparison to other RDF API approaches. Section 5.5 discusses our experiences with Sesame to date, and Section 5.6 looks into possible future developments. Finally, we provide our conclusions in Section 5.7.

Source

Towards the semantic Web: ontology-driven knowledge management. Eds.: J. Davies, u.a

Theme

Semantic Web

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Abstract

Innovative research institutes rely on the availability of complete and accurate information about new research and development, and it is the business of information providers such as Elsevier to provide the required information in a cost-effective way. It is very likely that the semantic web will make an important contribution to this effort, since it facilitates access to an unprecedented quantity of data. However, with the unremitting growth of scientific information, integrating access to all this information remains a significant problem, not least because of the heterogeneity of the information sources involved - sources which may use different syntactic standards (syntactic heterogeneity), organize information in very different ways (structural heterogeneity) and even use different terminologies to refer to the same information (semantic heterogeneity). The ability to address these different kinds of heterogeneity is the key to integrated access. Thesauri have already proven to be a core technology to effective information access as they provide controlled vocabularies for indexing information, and thereby help to overcome some of the problems of free-text search by relating and grouping relevant terms in a specific domain. However, currently there is no open architecture which supports the use of these thesauri for querying other data sources. For example, when we move from the centralized and controlled use of EMTREE within EMBASE.com to a distributed setting, it becomes crucial to improve access to the thesaurus by means of a standardized representation using open data standards that allow for semantic qualifications. In general, mental models and keywords for accessing data diverge between subject areas and communities, and so many different ontologies have been developed. An ideal architecture must therefore support the disclosure of distributed and heterogeneous data sources through different ontologies. The aim of the DOPE project (Drug Ontology Project for Elsevier) is to investigate the possibility of providing access to multiple information sources in the area of life science through a single interface.