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    Personal annotations in data visualizations transform collective storytelling. Reader comments on COVID-19 data visualizations foster empathy and personal reflection, becoming key focal points.

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    Area of Science:

    • Data Visualization
    • Human-Computer Interaction
    • Social Computing

    Background:

    • Critical cartography explores personal perspectives in mapping.
    • Data visualizations can be enhanced by user-generated content.
    • Collective storytelling leverages shared experiences for data interpretation.

    Purpose of the Study:

    • Investigate personal annotations in data visualizations for collective storytelling.
    • Understand how reader comments influence visualization interpretation.
    • Examine the role of social traces in data engagement.

    Main Methods:

    • Analysis of interaction logs and reader surveys.
    • Qualitative analysis of visualization annotations and interviews.
    • Studied user engagement with COVID-19 data visualizations.

    Main Results:

    • Reader annotations facilitate empathy and reflection on personal experiences.
    • Annotations act as social traces, guiding users through visualizations.
    • Embedded annotations often become the primary focus, overshadowing data encodings.

    Conclusions:

    • Personal perspectives in visualization annotations enable powerful collective data storytelling.
    • Social traces within visualizations enhance reader connection and contextualization.
    • Annotations significantly shape the understanding and focus of data visualizations.