Data integration: a theoretical perspective
Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Preserving mapping consistency under schema changes
The VLDB Journal — The International Journal on Very Large Data Bases
Query reformulation with constraints
ACM SIGMOD Record
Ontology change: Classification and survey
The Knowledge Engineering Review
Graceful database schema evolution: the PRISM workbench
Proceedings of the VLDB Endowment
Datalog±: a unified approach to ontologies and integrity constraints
Proceedings of the 12th International Conference on Database Theory
The PRISM Workwench: Database Schema Evolution without Tears
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Semantics and complexity of SPARQL
ACM Transactions on Database Systems (TODS)
Ontologies and Databases: The DL-Lite Approach
Reasoning Web. Semantic Technologies for Information Systems
On Detecting High-Level Changes in RDF/S KBs
ISWC '09 Proceedings of the 8th International Semantic Web Conference
Ontology and Schema Evolution in Data Integration: Review and Assessment
OTM '09 Proceedings of the Confederated International Conferences, CoopIS, DOA, IS, and ODBASE 2009 on On the Move to Meaningful Internet Systems: Part II
Journal on data semantics X
Exelixis: evolving ontology-based data integration system
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Ontology evolution: assisting query migration
ER'12 Proceedings of the 31st international conference on Conceptual Modeling
Ontology evolution without tears
Web Semantics: Science, Services and Agents on the World Wide Web
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The evolution of ontologies is an undisputed necessity in ontologybased data integration. In such systems ontologies are used as global schema in order to formulate queries that are answered by the data integration systems. Yet, few research efforts have focused on addressing the need to reflect ontology evolution onto the underlying data integration systems. In most of these systems, when ontologies change their relations with the data sources, i.e., the mappings, are recreated manually, a process which is known to be error-prone and timeconsuming. In this paper, we provide a solution that allows query answering under evolving ontologies without mapping redefinition. To achieve that, query rewriting techniques are exploited in order to produce equivalent rewritings among ontology versions. Whenever equivalent rewritings cannot be produced we a) guide query redefinition or b) provide the best "over-approximations". We show that our approach can greatly reduce human effort spent since continuous mapping redefinition on evolving ontologies is no longer necessary.