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dc.contributor.authorXu, Shenyuen_US
dc.contributor.authorBryan, Chrisen_US
dc.contributor.authorLi, Jianping Kelvinen_US
dc.contributor.authorZhao, Jianen_US
dc.contributor.authorMa, Kwan-Liuen_US
dc.contributor.editorJeffrey Heer and Heike Leitte and Timo Ropinskien_US
dc.description.abstractMany 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.en_US
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.titleChart Constellations: Effective Chart Summarization for Collaborative and Multi-User Analysesen_US
dc.description.seriesinformationComputer Graphics Forum
dc.description.sectionheadersComparative and Collaborative

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  • 37-Issue 3
    EuroVis 2018 - Conference Proceedings

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