Chart Constellations: Effective Chart Summarization for Collaborative and Multi-User Analyses
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Date
2018
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association and John Wiley & Sons Ltd.
Abstract
Many data problems in the real world are complex and require multiple analysts working together to uncover embedded insights by creating chart-driven data stories. How, as a subsequent analysis step, do we interpret and learn from these collections of charts? We present Chart Constellations, a system to interactively support a single analyst in the review and analysis of data stories created by other collaborative analysts. Instead of iterating through the individual charts for each data story, the analyst can project, cluster, filter, and connect results from all users in a meta-visualization approach. Constellations supports deriving summary insights about prior investigations and supports the exploration of new, unexplored regions in the dataset. To evaluate our system, we conduct a user study comparing it against data science notebooks. Results suggest that Constellations promotes the discovery of both broad and high-level insights, including theme and trend analysis, subjective evaluation, and hypothesis generation.
Description
@article{10.1111:cgf.13402,
journal = {Computer Graphics Forum},
title = {{Chart Constellations: Effective Chart Summarization for Collaborative and Multi-User Analyses}},
author = {Xu, Shenyu and Bryan, Chris and Li, Jianping Kelvin and Zhao, Jian and Ma, Kwan-Liu},
year = {2018},
publisher = {The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {10.1111/cgf.13402}
}