Combining the Best of Global-as-View and Local-as-View for Data Integration

Currently, there are two main basic approaches to data integration: Global-as-View (GaV) and Local-as-View (LaV). However, both GaV and LaV have their limitations. In a GaV approach, changes in information sources or adding a new information source requires revisions of a global schema and mappings between the global schema and source schemas. In a LaV approach, automating query reformulation has exponential time complexity with respect to query and source schema definitions. To resolve these problems, we offer BGLaV as an alternative point of view that is neither GaV nor LaV. The approach uses source-to-target mappings based on a predefined conceptual target schema, which is specified ontologically and independently of any of the sources. The proposed data integration system is easier to maintain than both GaV and LaV, and query reformulation reduces to rule unfolding. Compared with other data integration approaches, our approach combines the advantages of GaV and LaV, mitigates the disadvantages, and provides an alternative for flexible and scalable data integration.