Combibining Artificial Intelligence and Databases for Data Integration

Data integration is a problem at the intersection of the elds of Artiicial Intelligence and Database Systems. The goal of a data integration system is to provide a uniform interface to a multitude of data sources, whether they are within one enterprise or on the WorldWide Web. The key challenges in data integration arise because the data sources being integrated have been designed independently for autonomous applications, and their contents are related in subtle ways. As a result, a data integration system requires rich formalisms for describing contents of data sources and relating between contents of diierent sources. This paper discusses works aimed at applying techniques from Artiicial Intelligence to the problem of data integration. In addition to employing Knowledge Representation techniques for describing contents of information sources, projects have also made use of Machine Learning techniques for extracting data from sources and planning techniques for query optimization. The paper also outlines future opportunities for applying AI techniques in the context of data integration.