Schematic heterogeneity arises when information that is represented as data under one schema, is represented within the schema in another, for example as relation or class names. Schematic heterogeneity is an important class of heterogeneity that arises frequently in multimedia databases, semi-structured data and in integrating legacy data for data warehousing applications. Traditional query languages and view mechanisms are insufficient for reconciling and translating data between schematically heterogeneous schemas. The goal of this research project is to permit the cooperative use of schematically heterogeneous schemas and the data structured under these schemas. The project addresses the development of novel languages and techniques for: (1) the transformation and integration of schematically heterogeneous schemas; (2) the integrated querying of data from schematically heterogeneous schemas; and (3) the efficient evaluation of queries over integrated views. The techniques are analyzed for efficiency, correctness and completeness. In addition, the techniques are implemented within a heterogeneous repository of medical data. An evaluation of this implementation is used to refine and extend the results. The educational component of this project aims to enhance undergraduate and graduate participation in research, particularly among women and minority students. This is accomplished through curriculum enhancement, expanding undergraduate research opportunities and establishing academic enrichment programs for graduate minority students.
