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Computing How-Provenance for SPARQL Queries via Query Rewriting

Summary: SPARQLprov computes how-provenance polynomials for monotonic and non-monotonic SPARQL queries via query rewriting and spm-semirings. It is system-agnostic, requiring no engine extensions, yet achieves competitive overhead on standard SPARQL engines. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
hefa225c76316659a
Venue
VLDB
Year
2021
Pagerank
5.3533379e-05
Overall Rank
8,323 | 44.07%
DOI
10.14778/3484224.3484235
PDF
Download (CC BY-NC-ND 4.0)

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{hernandez_vldb21,
        title = {{Computing How-Provenance for SPARQL Queries via Query Rewriting}},
        author = {Hernández, Daniel and Galárraga, Luis and Hose, Katja},
        journal = {PVLDB},
        series = {{VLDB} '21},
        volume = {14},
        number = {13},
        pages = {3389--3401},
        doi = {10.14778/3484224.3484235},
        url = {https://doi.org/10.14778/3484224.3484235},
        year = {2021}
}

Incoming Citations (Sorted by Pagerank)

Showing 4 of 4 citing papers.

Rank Citing Paper Year Venue Pagerank
8,408 FaDE: More Than a Million What-ifs Per Second 2025 VLDB 5.3364407e-05
10,851 Bolt-on, Verifiable Provenance for LLM-Powered Data Processing 2026 VLDB 4.9769913e-05
10,888 Computing Why-Provenance for Property Graph Queries 2026 VLDB 4.9769913e-05
11,144 Unified Lineage System: Tracking Data Provenance at Scale 2025 SIGMOD 4.9769913e-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
17 Provenance Semirings 2007 PODS 0.00059813669
811 Provenance for Aggregate Queries 2011 PODS 0.00013746145
1,812 ProvSQL: Provenance and Probability Management in PostgreSQL 2018 VLDB 9.5780882e-05
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