VisClean: Interactive Cleaning for Progressive Visualization
Summary: VisClean couples progressive visualization with visualization-aware, interactive data cleaning, exposing how dirty data distorts charts. Its GUI lets users answer cleaning questions intuitively and substantially improve visualization quality with only a few interactions. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Yuyu Luo (Tsinghua University)
- 2. Chengliang Chai (Tsinghua University)
- 3. Xuedi Qin (Tsinghua University)
- 4. Nan Tang (Hamad Bin Khalifa University; Qatar Computing Research Institute)
- 5. Guoliang Li (Tsinghua University)
BibTeX Citation
@article{luo_vldb20,
title = {{VisClean: Interactive Cleaning for Progressive Visualization}},
author = {Luo, Yuyu and Chai, Chengliang and Qin, Xuedi and Tang, Nan and Li, Guoliang},
journal = {PVLDB},
series = {{VLDB} '20},
volume = {13},
number = {12},
pages = {2821--2824},
doi = {10.14778/3415478.3415484},
url = {https://doi.org/10.14778/3415478.3415484},
year = {2020}
}Incoming Citations (Sorted by Pagerank)
Showing 8 of 8 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,941 | GoodCore: Data-effective and Data-efficient Machine Learning through Coreset Selection over Incomplete Data | 2023 | SIGMOD | 6.9138042e-05 |
| 4,864 | Synthesizing Natural Language to Visualization (NL2VIS) Benchmarks from NL2SQL Benchmarks | 2021 | SIGMOD | 6.3770469e-05 |
| 5,495 | HAIChart: Human and AI Paired Visualization System | 2024 | VLDB | 6.1056297e-05 |
| 7,090 | LEAD: Iterative Data Selection for Efficient LLM Instruction Tuning | 2026 | VLDB | 5.601767e-05 |
| 7,258 | Learned Data-aware Image Representations of Line Charts for Similarity Search | 2023 | SIGMOD | 5.572114e-05 |
| 7,648 | MisDetect: Iterative Mislabel Detection using Early Loss | 2024 | VLDB | 5.4772833e-05 |
| 9,417 | Towards Observability for Production Machine Learning Pipelines | 2022 | VLDB | 5.1803615e-05 |
| 11,353 | UniClean: A Scalable Data Cleaning Solution for Mixed Errors based on Unified Cleaners and Optimized Cleaning Workflow | 2025 | VLDB | 4.9793485e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 4 of 4 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 530 | Magellan: Toward Building Entity Matching Management Systems | 2016 | VLDB | 0.00016855162 |
| 583 | Efficient Algorithms for Mining Outliers from Large Data Sets | 2000 | SIGMOD | 0.00015960125 |
| 1,099 | KATARA: A Data Cleaning System Powered by Knowledge Bases and Crowdsourcing | 2015 | SIGMOD | 0.00012037058 |
| 2,504 | Query-Oriented Data Cleaning with Oracles | 2015 | SIGMOD | 8.3782213e-05 |
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| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 12,177 | IHCS: An Integrated Hybrid Cleaning System | 2019 | VLDB |
| 2 | 1,043 | Data Cleaning: Overview and Emerging Challenges | 2016 | SIGMOD |
| 3 | 6,621 | A Demonstration of DBWipes: Clean as You Query | 2012 | VLDB |
| 4 | 204 | Declarative Data Cleaning: Language, Model, and Algorithms | 2001 | VLDB |
| 5 | 7,298 | CleanM: An Optimizable Query Language for Unified Scale-Out Data Cleaning | 2017 | VLDB |
| 6 | 8,695 | From Papers to Practice: The openclean Open-Source Data Cleaning Library | 2021 | VLDB |
| 7 | 483 | ActiveClean: Interactive Data Cleaning For Statistical Modeling | 2016 | VLDB |
| 8 | 9,747 | Arachnid: Generalized Visual Data Cleaning | 2019 | SIGMOD |
| 9 | 7,532 | PIClean: A Probabilistic and Interactive Data Cleaning System | 2019 | SIGMOD |
| 10 | 5,881 | ActiveClean: An Interactive Data Cleaning Framework For Modern Machine Learning | 2016 | SIGMOD |