Huge amounts of data available in a variety of digital forms has been collected and stored in thousands of repositories. However, the information relevant to a user or application need may b e s t o r e d i n m ultiple forms in di erent repositories. Answering a user query may require correlation of information at a semantic level across multiple forms and representations. We present a three-level architecture comprising of the ontology, metadata and data levels for enabling this correlation.

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... mponents of this architecture are explained by using an example from a GIS application. Metadata is the most critical level in our architecture. Various types of metadata developed by researchers for di erent media are reviewed and classi ed wrt the extent they model data or information content. The reference terms and the ontology of the metadata are classi ed wrt their dependence on the application domain. We identify the type of metadata suitable for enabling correlation at a semantic level. Issues of metadata extraction, storage and association with data are also discussed.