CAREER: Managing Schematic Heterogeneity in Database Management Systems

当在一个模式下表示为数据的信息在另一个模式中表示为关系或类名时，就会出现模式异构性。模式异构性是一类重要的异构性，它经常出现在多媒体数据库、半结构化数据以及为数据仓库应用程序集成遗留数据时。传统的查询语言和视图机制不足以在模式上不同的模式之间协调和转换数据。本研究项目的目标是允许合作使用图式上的异质图式以及在这些图式下构造的数据。该项目致力于开发新的语言和技术，用于：(1)转换和整合图式异质模式；(2)综合查询来自图式异类模式的数据；(3)对综合视图的查询进行有效评价。分析了这些技术的效率、正确性和完备性。此外，这些技术在医疗数据的异类存储库中实现。对这一执行情况的评估被用来改进和扩大结果。该项目的教育部分旨在加强本科生和研究生对研究的参与，特别是在妇女和少数族裔学生中。这是通过加强课程设置、扩大本科生研究机会和为少数民族研究生建立学术充实计划来实现的。

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.