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Conference Papers Year : 2022

Revisiting Semiring Provenance for Datalog

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.
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Dates and versions

hal-03771031 , version 1 (07-09-2022)

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Camille Bourgaux, Pierre Bourhis, Liat Peterfreund, Michaël Thomazo. Revisiting Semiring Provenance for Datalog. KR 2022 - 19th International Conference on Principles of Knowledge Representation and Reasoning, Jul 2022, Haifa, Israel. pp.91-101, ⟨10.24963/kr.2022/10⟩. ⟨hal-03771031⟩
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