Today many DataGrid applications need to manage and process a very large amount of data distributed across multiple grid nodes and stored into heterogeneous databases. Grids encourage and promote the publication, sharing and integration of scientifica data (distributed across several Virtual Organizations) in a more open manner than is currently the case, and many e-Science pojects have an urgent need to interconnect legacy and independently operated databases through a set os data access and integration services. The complexity of data management within a Computational Grid comes from the distribution, scale and heterogeneity of data sources. A set of dynamic and adaptive services could address specific issues related to automatic data management providing high performance and transparency as well as fully exploiting a grid infrastructure. These services should involved data migration and integration, discovery of data sources and so on, providing a transparent and dynamic layer of data virtualization. In this pape we introduce the Grid-DBMS concept, a framework for dynamic data management in a grid enviroment, highlighting its requirements, architecture, components and services. We also present an overview about the Grid Relational Catalog Project (GRelC) developed at the CACT/ISUFI of the University of Lecce, which represents a partial implementation of a Grid-DBMS for the Globus Community.
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