Towards Scalable Visual Data Wrangling via Direct Manipulation
Summary: Reframes cleaning as direct manipulation of coordinated views, letting users repair anomalies interactively and generate reproducible scripts. Scales via user-defined detectors/wranglers, provenance, differential storage and Hopara integration. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. El Kindi Rezig (University of Utah)
- 2. Mir Mahathir Mohammad (University of Utah)
- 3. Nicolas Baret (University of Utah)
- 4. Ricardo Mayerhofer (Hopara, Inc)
- 5. Andrew McNutt (University of Utah)
- 6. Paul Rosen (University of Utah)
BibTeX Citation
@inproceedings{rezig_cidr26,
address = {Amsterdam, Netherlands},
series = {{CIDR} '26},
title = {{Towards Scalable Visual Data Wrangling via Direct Manipulation}},
booktitle = {Proceedings of the {Conference} on {Innovative} {Data} {Systems} {Research}},
author = {Rezig, El Kindi and Mohammad, Mir Mahathir and Baret, Nicolas and Mayerhofer, Ricardo and McNutt, Andrew and Rosen, Paul},
year = {2026}
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