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Effective Data Integration in the Presence of Temporal Semantic Conflicts

By Hongwei Zhu, Stuart Madnick and Michael Siegel

Abstract

The change in meaning of data over time poses significant challenges for the use of that data. These challenges exist in the use of an individual data source and are further compounded with the integration of multiple sources. In this paper, we identify three types of temporal semantic heterogeneities, which have not been addressed by existing research. We propose a solution that is based on extensions to the Context Interchange framework. This approach provides mechanisms for capturing semantics using ontology and temporal context. It also provides a mediation service that automatically resolves semantic conflicts. We show the feasibility of this approach by demonstrating a prototype that implements a subset of the proposed extensi

Topics: Context Interchange framework, ontology and temporal context
Year: 2004
OAI identifier: oai:dspace.mit.edu:1721.1/7400
Provided by: DSpace@MIT

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