Many geoscientists use modern computational resources, such as software applications, Web services, scientific workflows and datasets that are readily available on the Internet, to support their research and many common tasks. These resources are often shared via human contact and sometimes stored in data portals; however, they are not necessarily available for metadata annotations that can assist in collaborative research or machine processing. Scientists' knowledge of their resources and processes are at risk of being lost. A scientist-driven discovery environment, which assumes a level of technical expertise generally possessed by a geoscientist, is needed to enable discovery and comparisons of computational entities. The goal of the research was to investigate an ontology-driven discovery approach that can be distributed on the Web and that can support the elicitation, documentation, and registration of computational entities and other resources. The main research efforts included: definition of a portal architecture that supports the registration, annotation, knowledge extraction and management, and discovery of computational resources using an ontology-driven approach; and evaluation of the usability and performance of a prototype system based on the architecture. The resulting innovative architecture blends Web 2.0 and Semantic Web technologies, features an intuitive and collaborative work environment of a structured wiki, and machine-interpretable metadata accessible via standard Semantic Web languages, such as RDF, SPARQL, and OWL. The ontology, called Computational Entity Discovery Ontology, provides a standard vocabulary for metadata acquisition encoded in standard Semantic Web languages OWL and RDF. The developed wiki is a next-generation structured wiki that not only delivers Web 2.0 advantages to provide a collaborative knowledge management environment, but also presents information in a well-arranged, structured fashion. The designed relational RDF repository features a unique user-customizable database schema generation approach based on the idea of horizontal partitioning. The experimental comparison with two known schema-oblivious and schema-aware database storage schemes showed superior performance of the proposed approach.
|Advisor:||Gates, Ann Q.|
|Commitee:||Chebotko, Artem, Keller, Randy, Kreinovich, Vladik|
|School:||The University of Texas at El Paso|
|School Location:||United States -- Texas|
|Source:||DAI-B 71/09, Dissertation Abstracts International|
|Subjects:||Information Technology, Computer science|
|Keywords:||Discovery ontology, Geosciences, Horizontal partitioning, Profile tables, Resource description framework, Semantic Web, Web 2.0|
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