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Evaluating Usability Aspects of a Mixed Reality Solution for Immersive Analytics in Industry 4.0 Scenarios
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Same Data, Different Audiences: Using Personas to Scope a Supercomputing Job Queue Visualization.

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    Guidepost is a novel notebook-embedded visualization designed to support diverse user groups. This approach balances broad utility with specific task support, enhancing overall data analysis effectiveness.

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    Area of Science:

    • Data Visualization
    • Human-Computer Interaction
    • Scientific Computing

    Background:

    • Domain-specific visualizations often limit utility to a single user group.
    • Designing for multiple user groups presents challenges and opportunities for broader applicability.
    • Balancing scope and specificity is key to enhancing visualization utility.

    Purpose of the Study:

    • To develop and evaluate Guidepost, a versatile notebook-embedded visualization.
    • To support diverse tasks across scientists, machine learning researchers, and system maintainers.
    • To explore the use of personas for categorizing tasks in visualization design.

    Main Methods:

    • Developed Guidepost, a visualization integrated within a notebook environment.
    • Adapted persona-based design to categorize tasks by stakeholder uniqueness.
    • Utilized interactive visualizations for shared tasks and scripting for unique tasks.
    • Evaluated Guidepost through real-world case studies and user evaluations.

    Main Results:

    • Guidepost effectively supports distinct tasks for scientists (compute wait times), machine learning researchers (prediction accuracy), and system maintainers (usage trends).
    • The visualization's visual encodings, interactions, and export capabilities cater to varied user needs.
    • Persona-based task categorization guided the design for multi-group support.

    Conclusions:

    • Guidepost demonstrates the value of a unified visualization approach for diverse data analysis needs.
    • Integrating interactive visualizations with scripting offers a flexible solution for complex data tasks.
    • Persona-driven design is effective for creating visualizations that serve multiple stakeholder groups.