Data Cleaning: Overview and Emerging Challenges
Summary: Presents a taxonomy of data cleaning, focusing on constraint- and pattern-based detection and repair for data quality. Links qualitative cleaning to ML and statistics, addressing scalability for big data and its impact on analytics, with a statistical view on inference. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Xu Chu (University of Waterloo)
- 2. Ihab F. Ilyas (University of Waterloo)
- 3. Sanjay Krishnan (University of California Berkeley)
- 4. Jiannan Wang (Simon Fraser University)
BibTeX Citation
@inproceedings{chu_sigmod16,
title = {{Data Cleaning: Overview and Emerging Challenges}},
author = {Chu, Xu and Ilyas, Ihab F. and Krishnan, Sanjay and Wang, Jiannan},
series = {{SIGMOD} '16},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/2882903.2912574},
url = {https://dl.acm.org/doi/10.1145/2882903.2912574},
year = {2016}
}
Incoming Citations (Sorted by Pagerank)
Showing 34 of 34 citing papers.
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 45 of 45 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 10,322 | Minimum Change ≠ Best Cleaning: Parallel and Incremental Error Detection under Integrity Constraints | 2026 | SIGMOD |
| 2 | 7,880 | Learning Over Dirty Data Without Cleaning | 2020 | SIGMOD |
| 3 | 3,580 | Automatic Data Repair: Are We Ready to Deploy? | 2024 | VLDB |
| 4 | 1,914 | Statistical Distortion: Consequences of Data Cleaning | 2012 | VLDB |
| 5 | 11,343 | Generalizable Data Cleaning of Tabular Data in Latent Space | 2024 | VLDB |
| 6 | 4,890 | Descriptive and Prescriptive Data Cleaning | 2014 | SIGMOD |
| 7 | 1,351 | Detecting Data Errors: Where are we and what needs to be done? | 2016 | VLDB |
| 8 | 1,484 | Data Quality and Data Cleaning: An Overview | 2003 | SIGMOD |
| 9 | 13,435 | Data Cleaning in the Era of Data Science: Challenges and Opportunities | 2021 | CIDR |
| 10 | 6,392 | Qualitative Data Cleaning | 2016 | VLDB |