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.
[1]
Klaus R. Dittrich,et al.
Data Provenance: A Categorization of Existing Approaches
,
2007,
BTW.
[2]
Sanjeev Khanna,et al.
Why and Where: A Characterization of Data Provenance
,
2001,
ICDT.
[3]
Gustavo Alonso,et al.
Provenance for nested subqueries
,
2009,
EDBT '09.
[4]
Jennifer Widom,et al.
Tracing the lineage of view data in a warehousing environment
,
2000,
TODS.
[5]
Gustavo Alonso,et al.
Perm: Processing Provenance and Data on the Same Data Model through Query Rewriting
,
2009,
2009 IEEE 25th International Conference on Data Engineering.