Mapping Discovery Over Revealing Schemas

Abstract

In a world of wide-scale information sharing, data are described in different formats, i.e. data structures, values and schemas. Querying such sources entails techniques that can bridge the data formats. Some existing techniques deal with schema mapping and view complementary aspects of the problem. Important ones, consider producing all the possible mappings for a pair of schemas, insinuating accompanying semantics in the mappings and adapting correct mappings as schemas evolve. In this work, we consider the problem of discovering mappings as schemas of autonomous sources are gradually revealed. Using as an example setting an overlay of peer databases, we present a schema mapping solution that discovers correct mappings as peer schemas are gradually revealed to remote peers. Mapping discovery is schema-centric and incorporates new semantics as they are unveiled. Mapping experience is reused and possible mappings are ranked so that the best choice is presented to the user. The experimental study confirms the suitability of the proposed solution to dynamic settings of heterogeneous sources.