New Challenges in Data Integration: Large Scale Automatic Schema Matching

Today schema matching is a basic problem in almost every data intensive distributed application, namely enterprise information integration, collaborating web services, ontology based agents communication, web catalogue integration and schema based P2P database systems. There has been a plethora of algorithms and techniques researched in schema matching and integration for data interoperability. Numerous surveys have been presented in the past to summerize this research. The requirement for extending the previous surveys has been created because of the mushrooming of the dynamic nature of these data intensive applications. Today data is viewed as a semantic entity, motivating new algorithms and strategies. The evolving large scale distributed information systems are further pushing the schema matching research to utilize the processing power not available in the past. Thus directly increasing the industry investment proportion in the matching domain. This article reviews the latest application domains in which schema matching is being utilized. It discusses the shift from manual to automatic schema matching, along with new definition of match covering the automation objectivity. Another panorama which is covered by this survey is the schema matching classification in the context of latest strategies and algorithms in the field of schema based information retrieval and management.