Semantic Matching across Heterogeneous Data Sources

As our ability to build information systems continues to grow, so does the need to integrate the systems we build. There is currently an urgent need for cooperation among massively distributed information systems for homeland security purposes. Information about a suspected individual needs to be retrieved from many systems maintained nationwide by various organizations, including intelligence agencies, police departments, motor vehicle departments, and airlines. There is also a need for a unified Master Patient Index (MPI) that integrates numerous healthcare information systems and allows authorized care providers to easily access the medical records of all patients [1]. The rapid growth of the Internet, especially the recent development of Web services, continuously amplifies the need for semantic interoperability across heterogeneous data sources. Related data sources accessible via different Web services create new requirements and opportunities for data integration. Such need for integration of information systems is becoming ubiquitous, both within and across organizations, in many domains. The information systems that need to be integrated are typically heterogeneous in several aspects; these include operating system, data model, database management system (DBMS)