VisClean: Interactive Cleaning for Progressive Visualization

Yuyu Luo; Chengliang Chai; Xuedi Qin; Nan Tang; Guoliang Li

doi:10.14778/3415478.3415484

VisClean: Interactive Cleaning for Progressive Visualization

Yuyu Luo, Chengliang Chai, Xuedi Qin, Nan Tang, Guoliang Li

Research output: Contribution to journal › Article › peer-review

17 Citations (Scopus)

Abstract

Data visualization is crucial in data-driven decision making. However, bad visualizations generated from dirty data often mislead the users to understand the data and to draw wrong decisions. We present VisClean, a system that can progressively visualize data with improved quality through interactive and visualization-aware data cleaning. We will demonstrate two main features of VisClean: (1) Easy-to-use: the users can easily answer data cleaning questions through a novel GUI; and (2) Cheap-to-clean: the quality of bad visualizations can be significantly improved in a few interactions.

Original language	English
Pages (from-to)	2821-2824
Number of pages	4
Journal	Proceedings of the VLDB Endowment
Volume	13
Issue number	12
DOIs	https://doi.org/10.14778/3415478.3415484
Publication status	Published - 2020
Externally published	Yes

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abstract = "Data visualization is crucial in data-driven decision making. However, bad visualizations generated from dirty data often mislead the users to understand the data and to draw wrong decisions. We present VisClean, a system that can progressively visualize data with improved quality through interactive and visualization-aware data cleaning. We will demonstrate two main features of VisClean: (1) Easy-to-use: the users can easily answer data cleaning questions through a novel GUI; and (2) Cheap-to-clean: the quality of bad visualizations can be significantly improved in a few interactions.",

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AU - Luo, Yuyu

AU - Chai, Chengliang

AU - Qin, Xuedi

AU - Tang, Nan

AU - Li, Guoliang

PY - 2020

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AB - Data visualization is crucial in data-driven decision making. However, bad visualizations generated from dirty data often mislead the users to understand the data and to draw wrong decisions. We present VisClean, a system that can progressively visualize data with improved quality through interactive and visualization-aware data cleaning. We will demonstrate two main features of VisClean: (1) Easy-to-use: the users can easily answer data cleaning questions through a novel GUI; and (2) Cheap-to-clean: the quality of bad visualizations can be significantly improved in a few interactions.

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VisClean: Interactive Cleaning for Progressive Visualization

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