Search (3 results, page 1 of 1)

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Abstract

Ontology construction is a labour-intensive and costly process. Even though many formal and semi-formal vocabularies are available, creating an ontology for a specific application is hindered in a number of ways. Firstly, the process of elicitating concepts is a time consuming and strenuous process. Secondly, it is difficult to keep focus. Thirdly, technical modelling constructs are hard to understand for the uninitiated. We propose ROC as a method to cope with these problems. ROC builds on well-known approaches for ontology construction. However, we reuse existing sources to generate a repository of proposed associations. ROC assists in efficiently putting forward all relevant concepts and relations by providing a large set of potential candidate associations. Secondly, rather than using intermediate representations of formal constructs we confront the domain expert with 'natural-language-like' statements generated from RDF-based triples. Moreover, we strictly separate the roles of problem owner, domain expert and knowledge engineer, each having his own responsibilities and skills. The domain expert and problem owner keep focus by monitoring a well-defined application purpose. We have implemented an initial set of tools to support ROC. This paper describes the ROC method and two application cases in which we evaluate the overall approach.

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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.

Type

a

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Abstract

This thesaurus-based search system uses automatic indexing, RDF-based querying, and concept-based visualization of results to support exploration of large online document repositories. Innovative research institutes rely on the availability of complete and accurate information about new research and development. Information providers such as Elsevier make it their business to provide the required information in a cost-effective way. The Semantic Web will likely contribute significantly to this effort because it facilitates access to an unprecedented quantity of data. The DOPE project (Drug Ontology Project for Elsevier) explores ways to provide access to multiple lifescience information sources through a single interface. With the unremitting growth of scientific information, integrating access to all this information remains an important problem, primarily because the information sources involved are so heterogeneous. Sources might use different syntactic standards (syntactic heterogeneity), organize information in different ways (structural heterogeneity), and even use different terminologies to refer to the same information (semantic heterogeneity). Integrated access hinges on the ability to address these different kinds of heterogeneity. Also, mental models and keywords for accessing data generally diverge between subject areas and communities; hence, many different ontologies have emerged. An ideal architecture must therefore support the disclosure of distributed and heterogeneous data sources through different ontologies. To serve this need, we've developed a thesaurus-based search system that uses automatic indexing, RDF-based querying, and concept-based visualization. We describe here the conversion of an existing proprietary thesaurus to an open standard format, a generic architecture for thesaurus-based information access, an innovative user interface, and results of initial user studies with the resulting DOPE system.

Content

Vgl.: Waard, A. de, C. Fluit u. F. van Harmelen: Drug Ontology Project for Elsevier (DOPE). In: http://www.w3.org/2001/sw/sweo/public/UseCases/Elsevier/Elsevier_Aduna_VU.pdf.

Type

a