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Semantic-based Data Source Discovery for DAI

The problem of data source discovery is a key issue in a data access and integration (DAI) system in the grid environment. This problem involves assigning data sources to tasks in order to satisfy task requirements and data source policies. These requirements and policies are often expressed in disjoint application and data source models, forcing a data source selector to perform semantic matching between the two. This paper addresses the need of semantic component in the grid environment to discover and describe the data sources semantically. In this paper, we propose a flexible and extensible approach for solving the problem of data source matching and selection using semantic web technologies. We design an ontology-based data source selector that exploits ontologies, background knowledge, and rules to discover suitable data sources in the Grid.