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. We propose a solution based on extensions to the context interchange framework, which has 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 with a prototype that implements a subset of the proposed extensions.
['Hongwei Zhu', 'Stuart E. Madnick', 'Michael Siegel']
Effective data integration in the presence of temporal semantic conflicts