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Computing How-Provenance for SPARQL Queries via Query Rewriting

Summary: SPARQLprov rewrites SPARQL to compute how-provenance polynomials for graphs. System-agnostic; uses spm-semirings to ensure provenance commutes with homomorphisms for monotonic and non-monotonic SPARQL; experiments show acceptable overhead and competitiveness. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
12548
Venue
VLDB
Year
2021
Pagerank
4.4206222e-05
Overall Rank
8,960 | 37.67%
DOI
10.14778/3484224.3484235

Incoming Non-self Citations Over Time

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Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
10,419 Unified Lineage System: Tracking Data Provenance at Scale 2025 SIGMOD 4.1945683e-05
10,886 FaDE: More Than a Million What-ifs Per Second 2025 VLDB 4.1945683e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 3 of 3 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
1,106 Provenance for Aggregate Queries 2011 PODS 0.0001398766
2,256 ProvSQL: Provenance and Probability Management in PostgreSQL 2018 VLDB 9.1879032e-05
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