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Roslingifier: Semi-Automated Storytelling for Animated Scatterplots.

Minjeong Shin, Joohee Kim, Yunha Han

    IEEE Transactions on Visualization and Computer Graphics
    |January 27, 2022
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    Summary

    Roslingifier is a new method for data storytelling using animated scatterplots. It helps presenters create engaging data narratives with automated tools, enhancing audience insights.

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    Area of Science:

    • Data Visualization
    • Human-Computer Interaction
    • Information Design

    Background:

    • Animated scatterplots are powerful tools for data exploration.
    • Data-driven storytelling techniques are emerging but lack systematic study.
    • Interactive visualizations require effective presentation methods for audience engagement.

    Purpose of the Study:

    • To introduce Roslingifier, a novel data-driven storytelling method for animated scatterplots.
    • To define the design space for data presentation in this new genre.
    • To develop a semi-automated authoring tool to aid presenters.

    Main Methods:

    • Analysis of video clips of presentations using interactive visualizations.
    • Derivation of three key techniques: natural language narratives, visual effects, and temporal branching.
    • Implementation of Roslingifier with automated identification, clustering, and narrative generation.

    Main Results:

    • Roslingifier enables effective creation of engaging data stories.
    • The system features facilitate diverse insights for both presenters and viewers.
    • User studies confirmed the method's effectiveness in data presentation.

    Conclusions:

    • Roslingifier represents a new genre of data-driven storytelling.
    • The developed authoring tool supports the creation of quality data presentations.
    • This method enhances audience understanding and discovery of insights from data.