Defining and Using Schematic Correspondences for Automatically Generating Schema Mappings

Mapping specification has been recognised as a critical bottleneck to the large scale deployment of data integration systems. A mapping is a description using which data structured under one schema are transformed into data structured under a different schema, and is central to data integration and data exchange systems. In this paper, we argue that the classical approach of correspondence identification followed by (manual) mapping generation can be simplified through the removal of the second step by judicious refinement of the correspondences captured. As a step in this direction, we present in this paper a model for schematic correspondences that builds on and extends the classification proposed by Kim et al. to cater for the automatic derivation of mappings, and present an algorithm that shows how correspondences specified in the model proposed can be used for deriving schema mappings. The approach is illustrated using a case study from integration in proteomics.