Boris Glavic
Gustavo Alonso
ABSTRACT
In this demonstration we present the Perm provenance management system (PMS). Perm is capable of computing, storing and querying provenance information for the relational data model. Provenance is computed by using query rewriting techniques to annotate tuples with provenance information. Thus, provenance data and provenance computations are represented as relational data and queries and, hence, can be queried, stored and optimized using standard relational database techniques. This demo shows the complete Perm system and lets attendants examine in detail the process of query rewriting and provenance retrieval in Perm, the most complete data provenance system available today. For example, Perm supports lazy and eager provenance computation, external provenance and various contribution semantics.
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Digital Library
- Y. Cui, J. Widom, and J. L. Wiener. Tracing the lineage of view data in a warehousing environment. ACM Transactions on Database Systems, 25(2):179--227, 2000. Google ScholarDigital Library
- B. Glavic and G. Alonso. Perm: Processing provenance and data on the same data model through query rewriting. In ICDE'09, 2009. Google ScholarDigital Library
- B. Glavic and G. Alonso. Provenance for nested subqueries. In EDBT'09, 2009. Google ScholarDigital Library
- B. Glavic and K. R. Dittrich. Data provenance: A categorization of existing approaches. In BTW'07, pages 227--241, 2007.Google Scholar
Index Terms
- The perm provenance management system in action
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