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Detecting Data Errors: Where are we and what needs to be done?

Summary: Empirical study: data-cleaning tools miss large portions of real-world errors and have robustness gaps. Proposes multi-tool workflow to boost coverage with less verification; notes domain-specific tools and enrichment, but some errors remain undetectable. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
hf589acc29fcb027c
Venue
VLDB
Year
2016
Pagerank
0.00011076619
Overall Rank
1,306 | 91.25%
DOI
10.14778/2994509.2994518
PDF
Download (CC BY-NC-ND 4.0)

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{abedjan_vldb16,
        title = {{Detecting Data Errors: Where are we and what needs to be done?}},
        author = {Abedjan, Ziawasch and Chu, Xu and Deng, Dong and Fernandez, Raul Castro and Ilyas, Ihab F. and Ouzzani, Mourad and Papotti, Paolo and Stonebraker, Michael and Tang, Nan},
        journal = {PVLDB},
        series = {{VLDB} '16},
        volume = {9},
        number = {12},
        pages = {993--1004},
        doi = {10.14778/2994509.2994518},
        url = {https://doi.org/10.14778/2994509.2994518},
        year = {2016}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 51 citing papers.

Rank Citing Paper Year Venue Pagerank
12,080 GEDet: Detecting Erroneous Nodes with A Few Examples 2021 VLDB 4.9605343e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 13 of 13 cited papers.

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

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