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    Summary
    This summary is machine-generated.

    MEDLEY simplifies dashboard creation by recommending relevant visualization collections based on user analytical intents. This mixed-initiative interface aids users in building effective analytic dashboards more efficiently.

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    Area of Science:

    • Human-Computer Interaction
    • Data Visualization
    • Software Engineering

    Background:

    • Dashboard authoring is complex and time-consuming.
    • Existing tools lack support for discovering useful visualization groups for dashboards.

    Purpose of the Study:

    • To present MEDLEY, a mixed-initiative interface for assisting dashboard composition.
    • To recommend dashboard collections mapped to specific analytical intents.

    Main Methods:

    • MEDLEY uses user-specified analytical intents (e.g., measure, change, category, distribution analysis) or implicit selections.
    • The system recommends collections of visualizations and filtering widgets.
    • A direct manipulation interface allows configuration of view interactions.

    Main Results:

    • MEDLEY's recommendations guide dashboard composition.
    • The interface facilitates diverse user workflows for creating analytic dashboards.
    • A user study with 13 participants informed the findings.

    Conclusions:

    • MEDLEY effectively assists in dashboard composition by recommending relevant visualization collections.
    • Future work includes integrating manual specification with recommendations and exploring natural language interfaces for dashboard authoring.