Research Papers
Intelligent resource discovery using ontology-based resource profiles
Authors:
J Steven Steven ,
Jet Propulsion Laboratory, 4800 Oak Grove Drive, Pasadena, California, 91109 USA, US
Dan Crichton,
Jet Propulsion Laboratory, 4800 Oak Grove Drive, Pasadena, California, 91109 USA, US
Sean Kelly,
Jet Propulsion Laboratory, 4800 Oak Grove Drive, Pasadena, California, 91109 USA, US
Chris A Mattmann,
Jet Propulsion Laboratory, 4800 Oak Grove Drive, Pasadena, California, 91109 USA, US
Jerry Crichton,
Jet Propulsion Laboratory, 4800 Oak Grove Drive, Pasadena, California, 91109 USA, US
Thuy Tran
Jet Propulsion Laboratory, 4800 Oak Grove Drive, Pasadena, California, 91109 USA, US
Abstract
Successful resource discovery across heterogeneous repositories is highly dependent on the semantic and syntactic homogeneity of the associated resource descriptions in each repository. Ideally, consistent resource descriptions are easily extracted from each repository, expressed using standard syntactic and semantic structures, and managed and accessed within a distributed, flexible, and scalable software framework. In practice however, seldom do all three of these elements exist. To help address this situation, the Object Oriented Data Technology (OODT) project at the Jet Propulsion Laboratory has developed an extensible, standards-based resource description scheme that provides the necessary description and management facilities for the discovery of resources across heterogeneous repositories. The OODT resource description scheme can be used across scientific domains to describe any resource. It uses a small set of generally accepted, broadly-scoped descriptors while also providing a mechanism for the inclusion of domain-specific descriptors. In addition, the OODT scheme can be used to capture hierarchical, relational and recursive relationships between resources. In this paper we expand on prior work and describe an intelligent resource discovery framework that consists of separate software and data architectures focusing on the standard resource description scheme. We illustrate intelligent resource discovery using a case study that provides efficient search across distributed repositories using common interfaces and a hierarchy of resource descriptions derived from a complex, domain-specific ontology.
How to Cite:
Steven, J.S. et al., (2006). Intelligent resource discovery using ontology-based resource profiles. Data Science Journal. 4, pp.171–188. DOI: http://doi.org/10.2481/dsj.4.171
Published on 25 Jan 2006.
Peer Reviewed
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