Framework and Knowledge for Database Integration

Publication Type

Conference Proceeding Article

Publication Date



Traditionally, data integration research has focused primarily on understanding integration issues from the data instance and schema perspectives. However, when the integration of heterogeneous databases is performed without considering the semantics of local databases, an incorrectly integrated database may result. Moreover, most integration tasks must be performed manually. In this research, we propose a framework for acquiring the appropriate domain semantics and various types of knowledge needed to detect and reconcile heterogeneities among local databases. By (semi-)automating the acquisition and maintenance of these semantics and knowledge, coupled with an expert system that performs reasoning over these knowledge, database integration processes can be performed at a higher level of automation. This research introduces a database integration framework. The proposed framework provides a foundation to: 1) analyze database integration issues from a broad scope, 2) discuss the impact of database reverse engineering on database integration, 3) distinguish the data warehousing approach from the federated database approach for global query processing and instance integration, and 4) identify various types of knowledge that are required for proper data integration. A systematic classification of these knowledge will facilitate the design of appropriate techniques to acquire and utilize them.


Information technology, Integrated database, Implementation, Firm, Engineering, Methodology, Performance evaluation, Knowledge based, Knowledge structure


Databases and Information Systems

Research Areas

Data Management and Analytics


Managing Information Technology Resources and Applications in the World Economy: Proceedings of the 1997 Information Resources Management Association International Conference, Vancouver, BC

First Page


Last Page





Idea Group

City or Country

Hershey, PA

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