New Challenges in Data Integration: Large Scale Automatic Schema Matching

Khalid Saleem 1 Zohra Bellahsene 2
2 ZENITH - Scientific Data Management
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier, CRISAM - Inria Sophia Antipolis - Méditerranée
Abstract : Today schema matching is a basic task 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 summarize 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. Indeed, evolving large scale distributed information systems are further pushing the schema matching research to utilize the processing power not available in the past and directly increasing the industry investment proportion in the matching domain. This article reviews the latest application domains in which schema matching is being utilized. The paper gives a detailed insight about the desiderata for schema matching and integration in the large scale scenarios. Another panorama which is covered by this survey is the shift from manual to automatic schema matching. Finally the paper presents the state of the art in large scale schema matching, classifying the tools and prototypes according to their input, output and execution strategies and algorithms.
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Contributeur : Khalid Saleem <>
Soumis le : mercredi 16 avril 2008 - 03:36:53
Dernière modification le : jeudi 24 mai 2018 - 15:59:21
Document(s) archivé(s) le : mardi 21 septembre 2010 - 16:10:16


  • HAL Id : lirmm-00170765, version 2



Khalid Saleem, Zohra Bellahsene. New Challenges in Data Integration: Large Scale Automatic Schema Matching. 2007. 〈lirmm-00170765v2〉



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