Schema Level and Data Level Mapping Composition

Schema mappings and data mappings constitute essential building blocks of data integration, data exchange and peer-to-peer data sharing systems. At present, either schema-level mappings or datalevel mappings are used for data sharing purposes. In this paper we consider the semantics of bi-level mapping that combines the schema-level and data-level mappings. Tabular representation of the mappings helps to solve many mapping-related algorithmic and semantic problems, like mapping composition. Composition of mappings between sources has several computational advantages in a peer data sharing system, such as yielding more efficient query translation and pruning redundant paths. Considering the need of mapping composistion, this paper presents a mechanism for composing two bi-level mappings by using tableaux.