Provenance for nested subqueries
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
The perm provenance management system in action
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
Efficient querying and maintenance of network provenance at internet-scale
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Research issues in data provenance
Proceedings of the 48th Annual Southeast Regional Conference
Automatic rule refinement for information extraction
Proceedings of the VLDB Endowment
TRAMP: understanding the behavior of schema mappings through provenance
Proceedings of the VLDB Endowment
The Foundations for Provenance on the Web
Foundations and Trends in Web Science
Provenance based conflict handling strategies
DASFAA'12 Proceedings of the 17th international conference on Database Systems for Advanced Applications
Efficient provenance storage for relational queries
Proceedings of the 21st ACM international conference on Information and knowledge management
International Journal of Systems and Service-Oriented Engineering
SPADE: support for provenance auditing in distributed environments
Proceedings of the 13th International Middleware Conference
Algebraic structures for capturing the provenance of SPARQL queries
Proceedings of the 16th International Conference on Database Theory
Ariadne: managing fine-grained provenance on data streams
Proceedings of the 7th ACM international conference on Distributed event-based systems
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Data provenance is information that describes how a given data item was produced. The provenance includes source and intermediate data as well as the transformations involved in producing the concrete data item. In the context of a relational databases, the source and intermediate dataitems are relations, tuples and attribute values. The transformations are SQL queries and/or functions on the relational data items. Existing approaches capture provenance information by extending the underlying data model. This has the intrinsic disadvantage that the provenance must be stored and accessed using a different model than the actual data. In this paper, we present an alternative approach that uses query rewriting to annotate result tuples with provenance information. The rewritten query and its result use the same model and can, thus, be queried, stored and optimized using standard relational database techniques. In the paper we formalize the query rewriting procedures, prove their correctness, and evaluate a first implementation of the ideas using PostgreSQL. As the experiments indicate, our approach efficiently provides provenance information inducing only a small overhead on normal operations.