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The Complexity of Why-Provenance for Datalog Queries

Summary: Data- and complexity-theoretic analysis of why-provenance for Datalog queries, filling a literature gap with a sharp dichotomy. Recursive (even linear) Datalog why-provenance is intractable; non-recursive cases are highly tractable. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
1914
Venue
PODS
Year
2024
Pagerank
4.5797807e-05
Overall Rank
8,125 | 43.48%
DOI
10.1145/3651146

Incoming Non-self Citations Over Time

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Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank Citing Paper Year Venue Pagerank
9,813 Datalog with First-Class Facts 2025 VLDB 4.2783272e-05
10,344 Circuits and Formulas for Datalog over Semirings 2025 PODS 4.1945683e-05
10,922 Below and Above Why-Provenance for Datalog Queries 2024 PODS 4.1945683e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 4 of 4 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
31 Provenance Semirings 2007 PODS 0.0007857786
602 On the Complexity of Bounded-Variable Queries 1995 PODS 0.00019352415
2,764 The Semiring Framework for Database Provenance 2017 PODS 8.1574444e-05
2,907 Convergence of Datalog over (Pre-) Semirings 2022 PODS 7.933806e-05
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