Unified Data Model for Large-Scale Multi-Schema Integration (ULMI)

Abstract

Current approaches in schema mapping and matching focus on pair-wise comparison of schemas. This chapter gives an overview of how n-way comparison of schemas via a unified data model for large-scale multi-schema integration (ULMI) can benefit to schema matching and mapping processes. The approach integrates a set of input schemas into one comprehensive representation. Thus, a unified data model is constructed. The unified data model represents the closure of all integrated schemas. However, as the unified data model is too complex and too large, it is never revealed to the user. Therefore, the authors derive a canonical data model which represents the most common structure of all schemas. In a use case, the advantages of the canonical data model are demonstrated. Finally, challenges for further research are derived. This work is based on excerpts from realistic input schemas, and it provides a concrete, ideal canonical data model as a reference for further research.