Arachnid: Generalized Visual Data Cleaning

Summary: Arachnid generalizes visual data cleaning by translating mouse interactions on common visualizations into a broad set of cleaning transformations. Based on generalized selection and direct manipulation, it enables exploration-driven, on-the-fly cleaning beyond fixed pipelines. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 5701
Venue: SIGMOD
Year: 2019
Pagerank: 5.2528121e-05
Overall Rank: 9,571 | 34.34%
DOI: 10.1145/3299869.3300108

Incoming Non-self Citations Over Time

Authors

1. Conder L. Shou (Columbia University)
2. Amita Shukla (Columbia University)

BibTeX Citation

@inproceedings{shou_sigmod19,
        title = {{Arachnid: Generalized Visual Data Cleaning}},
        author = {Shou, Conder L. and Shukla, Amita},
        series = {{SIGMOD} '19},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3299869.3300108},
        url = {https://dl.acm.org/doi/10.1145/3299869.3300108},
        year = {2019}
}

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
10,131	Towards Scalable Visual Data Wrangling via Direct Manipulation	2026	CIDR	5.093636e-05

Outgoing Citations (Sorted by Pagerank)

Showing 0 of 0 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank

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