Schema Evolution publication categorizer

To enable modern data intensive applications we must solve the data mapping problem in which a source (legacy) database is mapped into a different, but fixed, target schema. Schema mapping involves the discovery of a query or a set of queries that transform the source data into the new structure. We introduce an interactive mapping creation paradigm based on value correspondences that show how a value of a target attribute can be created from a set of values of source attributes. We describe the use of the value correspondence framework in Clio, a prototype tool for semi-automated schema mapping, and present an algorithm for query derivation from an evolving set of value correspondences.