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In an increasing number of scientific disciplines, large data collections are emerging as important community resources. In this paper, we introduce design principles for a data management architecture called the data grid. We describe two basic services that we believe are fundamental to the design of a data grid, namely, storage systems and metadata management. Next, we explain how these services can be used to develop higher-level services for replica management and replica selection. We conclude by describing our initial implementation of data grid functionality.