In this paper, we describe and situate the system for data mapping in relational databases. Automating the discovery of mappings between structured data sources is a long standing and important problem in data management. Starting from user provided example instances of the source and target schemas, approaches mapping discovery as search within the transformation space of these instances based on a set of mapping operators. mapping expressions incorporate not only data-metadata transformations, but also simple and complex semantic transformations, resulting in significantly wider applicability than previous systems. Extensive empirical validation of , both on synthetic and real world datasets, indicates that the approach is both viable and effective.
|Title of host publication
|Proceedings of the 10th International Conference on Extending Database Technology: Advances in Database Technology (EDBT 2006), 26-31 March 2006, Munich, Germany
|Y. Ioannidis, M.H. Scholl, J.W. Schmidt, F. Matthes, M. Hatzopoulos, K. Böhm, A. Kemper, T. Grust, C. Böhm
|Place of Publication
|Published - 2006
|Lecture Notes in Computer Science