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We describe a testbed for database selection techniques and an experiment conducted using this testbed. The testbed is a decomposition of the TREC/TIPSTER data that allows analysis of the data along multiple dimensions, including collection-based and temporal-based analysis. We characterize the subcollections in this testbed in terms of number of documents, queries against which the document, s have been evaluated for relevance, and distribution of relevant documents. We then present initial results from a study conducted using this testbed that examines the effectiveness of the gGlOSS approach to database selection. The databases from our testbed were ranked using the gGl0S. S techniques and compared to the gGlOSS I&l (l) baseline and a baseline derived from TREC relevance judgements. We have examined the degree to which several gGlOSS estimate functions approximate these baselines. Our …