A Transparent Schema-Evolution System Based on Object-Oriented View Technology
IEEE Transactions on Knowledge and Data Engineering
The EVE Approach: View Synchronization in Dynamic Distributed Environments
IEEE Transactions on Knowledge and Data Engineering
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EDBT '96 Proceedings of the 5th International Conference on Extending Database Technology: Advances in Database Technology
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EKAW '02 Proceedings of the 13th International Conference on Knowledge Engineering and Knowledge Management. Ontologies and the Semantic Web
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DILS '08 Proceedings of the 5th international workshop on Data Integration in the Life Sciences
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ISWC'05 Proceedings of the 4th international conference on The Semantic Web
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ISWC'05 Proceedings of the 4th international conference on The Semantic Web
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ISWC'05 Proceedings of the 4th international conference on The Semantic Web
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ISWC'05 Proceedings of the 4th international conference on The Semantic Web
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ISWC'06 Proceedings of the 5th international conference on The Semantic Web
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ESWC'05 Proceedings of the Second European conference on The Semantic Web: research and Applications
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CAiSE'12 Proceedings of the 24th international conference on Advanced Information Systems Engineering
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Web Semantics: Science, Services and Agents on the World Wide Web
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The development of new techniques and the emergence of new high- throughput tools have led to a new information revolution. The amount and the diversity of the information that need to be stored and processed have led to the adoption of data integration systems in order to deal with information extraction from disparate sources. The mediation between traditional databases and ontologies has been recognized as a cornerstone issue in bringing in legacy data with formal semantic meaning. However, our knowledge evolves due to the rapid scientific development, so ontologies and schemata need to change in order to capture and accommodate such an evolution. When ontologies change, these changes should somehow be rendered and used by the pre-existing data integration systems, a problem that most of the integration systems seem to ignore. In this paper, we review existing approaches for ontology/schema evolution and examine their applicability in a state-of-the-art, ontology-based data integration setting. Then, we show that changes in schemata differ significantly from changes in ontologies. This strengthens our position that current state of the art systems are not adequate for ontology-based data integration. So, we give the requirements for an ideal data integration system that will enable and exploit ontology evolution.