Interaction Techniques for Visual Exploration Using Embedded Word-Scale Visualizations

Interactive Data VisualizationTime-Series & Network Graph VisualizationUI/UX DesignersData Scientists & Analysts

We describe a design space of view manipulation interactions for small data-driven contextual visualizations (word-scale visualizations). These interaction techniques support an active reading experience and engage readers through exploration of embedded visualizations whose placement and content connect them to specific terms in a document. A reader could, for example, use our proposed interaction techniques to explore word-scale visualizations of stock market trends for companies listed in a market overview article. When readers wish to engage more deeply with the data, they can collect, arrange, compare, and navigate the document using the embedded word-scale visualizations, permitting more visualization-centric analyses. We support our design space with a concrete implementation, illustrate it with examples from three application domains, and report results from two experiments. The experiments show how view manipulation interactions helped readers examine embedded visualizations more quickly and with less scrolling and yielded qualitative feedback on usability and future opportunities.

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https://hci.top/en/papers/chi/32272/2020

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DOI: https://doi.org/10.1145/3313831.3376842
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Source
CHI
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Year
2020
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4 authors
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Subtopics
Interactive Data Visualization, Time-Series & Network Graph Visualization
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Professions
UI/UX Designers, Data Scientists & Analysts
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Abstract only
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