Revisiting Semiring Provenance for Datalog

Camille Bourgaux, Pierre Bourhis, Liat Peterfreund, Michaël Thomazo

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

4 Scopus citations

Abstract

Data provenance consists in bookkeeping meta information during query evaluation, in order to enrich query results with their trust level, likelihood, evaluation cost, and more. The framework of semiring provenance abstracts from the specific kind of meta information that annotates the data. While the definition of semiring provenance is uncontroversial for unions of conjunctive queries, the picture is less clear for Datalog. Indeed, the original definition might include infinite computations, and is not consistent with other proposals for Datalog semantics over annotated data. In this work, we propose and investigate several provenance semantics, based on different approaches for defining classical Datalog semantics. We study the relationship between these semantics, and introduce properties that allow us to analyze and compare them.

Original languageEnglish
Title of host publication19th International Conference on Principles of Knowledge Representation and Reasoning, KR 2022
PublisherInternational Joint Conferences on Artificial Intelligence
Pages91-101
Number of pages11
ISBN (Electronic)9781956792010
StatePublished - 2022
Externally publishedYes
Event19th International Conference on Principles of Knowledge Representation and Reasoning, KR 2022 - Haifa, Israel
Duration: 31 Jul 20225 Aug 2022

Publication series

Name19th International Conference on Principles of Knowledge Representation and Reasoning, KR 2022

Conference

Conference19th International Conference on Principles of Knowledge Representation and Reasoning, KR 2022
Country/TerritoryIsrael
CityHaifa
Period31/07/225/08/22

Bibliographical note

Publisher Copyright:
© 19th International Conference on Principles of Knowledge Representation and Reasoning, KR 2022. All rights reserved.

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