Integrating Data Sources Using a Standardized Global Dictionary

Abstract

With the constantly increasing reliance on database systems to store, process, and display data comes the additional problem of using these systems properly. Most organizations have several data systems that must work together. As data warehouses, data marts, and other OLAP systems are added to the mix, the complexity of ensuring interoperability between these systems increases dramatically. Interoperability of database systems can be achieved by capturing the semantics of each system and providing a standardized framework for querying and exchanging semantic specifications.

Our work focuses on capturing the semantics of data stored in databases with the goal of integrating data sources within a company, across a network, and even on the World-Wide Web. Our approach to capturing data semantics revolves around the definition of a global dictionary that provides standardized terms for referencing and categorizing data. These standardized terms are then stored in record-based semantic specifications that store metadata and semantic descriptions of the data. Using these semantic specifications, it is possible to integrate diverse data sources even though they were not originally designed to work together.

A prototype of this integration system called the Relational Integration Model (RIM) has been built. This paper describes the architecture and benefits of the system, and its possible applications. The RIM application is currently being tested on production database systems and integration problems.