Description

A common task in many database applications is the migration of legacy data from multiple sources into a new one. This requires identifying semantically related elements of the source and target systems and the mapping expressions to transform instances of those elements from the source format to the target format. Currently, data migration is typically done manually, a tedious and time-consuming process, which is difficult to scale to a high number of data sources. In this paper, we describe QuickMig, a new semi-automatic approach to determining semantic correspondences between schema elements for data migration applications. QuickMig advances the state of the art with a set of new techniques exploiting sample instances, domain ontologies, and reuse of existing mappings to detect not only element correspondences but also their mapping expressions. QuickMig further includes new mechanisms to effectively incorporate domain knowledge of users into the match process. The results from a comprehensive evaluation using real-world schemas and data indicate high quality and practicability of the overall approach.

The QuickMig evaluation data sets can be found here.