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A Model for Fine-Grained Data Citation

Summary: Model to automatically generate fine-grained citations for arbitrary relational queries via citation views that attach citations to views and are composed to cover query results. Leverages query-rewriting and provenance to construct citations and outlines practical challenges. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
293
Venue
CIDR
Year
2017
Pagerank
5.093636e-05
Overall Rank
11,966 | 17.91%
DOI
-

Incoming Non-self Citations Over Time

No non-self incoming citations found for this paper in this database.

Authors

BibTeX Citation

@inproceedings{davidson_cidr17,
        address = {Amsterdam, Netherlands},
        series = {{CIDR} '17},
        title = {{A Model for Fine-Grained Data Citation}},
        booktitle = {Proceedings of the {Conference} on {Innovative} {Data} {Systems} {Research}},
        author = {Davidson, Susan B. and Deutch, Daniel and Milo, Tova and Silvello, Gianmaria},
        year = {2017}
}

Incoming Citations (Sorted by Pagerank)

Showing 4 of 4 citing papers.

Rank Citing Paper Year Venue Pagerank
10,077 ProvCite: Provenance-based Data Citation 2019 VLDB 5.1603976e-05
11,928 Data Citation: Giving Credit Where Credit is Due 2018 SIGMOD 5.093636e-05
11,972 Data Citation: a Computational Challenge 2017 PODS 5.093636e-05
13,535 Automating Data Citation in CiteDB 2017 VLDB -
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Outgoing Citations (Sorted by Pagerank)

Showing 2 of 2 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 0.00059843817
22 Data Integration: A Theoretical Perspective 2002 PODS 0.00056204792
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