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Locating resources of interest in a large resource-intensive environment is a challenging problem. In this paper we present research on addressing this problem through the development of a recommender system to aid in metadata discovery. Our recommender approach uses conversational case-based reasoning (CCBR), with semantic Web markup languages providing a standard form for case representation. We present our initial efforts in designing and developing ontologies for an Earthquake Simulation Grid, to use these to guide case retrieval, discuss how these are exploited in a prototype application, and identify future steps for this approach.