On provenance minimization

Yael Amsterdamer, Daniel Deutch, Tova Milo, Val Tannen

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Provenance information has been proved to be very effective in capturing the computational process performed by queries, and has been used extensively as the input to many advanced data management tools (e.g. view maintenance, trust assessment, or query answering in probabilistic databases). We study here the core of provenance information, namely the part of provenance that appears in the computation of every query equivalent to the given one. This provenance core is informative as it describes the part of the computational process that is inherent to the query. It is also useful as a compact input to the above mentioned data management tools. We study algorithms that, given a query, compute an equivalent query that realizes the core provenance for all tuples in its result. We study these algorithms for queries of varying expressive power. Finally, we observe that, in general, one would not want to require database systems to evaluate a specific query that realizes the core provenance, but instead to be able to find, possibly off-line, the core provenance of a given tuple in the output (computed by an arbitrary equivalent query), without rewriting the query. We provide algorithms for such direct computation of the core provenance.

Original languageEnglish
Title of host publicationPODS'11 - Proceedings of the 30th Symposium on Principles of Database Systems
Pages141-152
Number of pages12
DOIs
StatePublished - 2011
Event30th Symposium on Principles of Database Systems, PODS'11 - Athens, Greece
Duration: 13 May 201115 May 2011

Publication series

NameProceedings of the ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems

Conference

Conference30th Symposium on Principles of Database Systems, PODS'11
Country/TerritoryGreece
CityAthens
Period13/05/1115/05/11

Fingerprint

Dive into the research topics of 'On provenance minimization'. Together they form a unique fingerprint.

Cite this