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    This survey provides a systematic overview of ensemble visualization techniques and analytic tasks from the last decade. It identifies research trends and future opportunities in visualizing complex ensemble data.

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    Area of Science:

    • Computer Science
    • Information Visualization
    • Data Science

    Background:

    • Ensemble visualization has significantly advanced due to increased ensemble data availability and diverse disciplinary needs.
    • Existing research often focuses on similar aspects of ensemble data, lacking a systematic overview for researchers.
    • A comprehensive survey is needed to identify research gaps and guide future developments in ensemble visualization.

    Purpose of the Study:

    • To provide a systematic survey of ensemble visualization research from the past decade.
    • To categorize existing works based on visualization techniques and analytic tasks.
    • To identify emerging trends and future research opportunities in the field.

    Main Methods:

    • Conducted a holistic review of ensemble visualization literature from the last decade.
    • Categorized studies from two perspectives: proposed visualization techniques and involved analytic tasks.
    • Analyzed adaptations of conventional visualization methods and differences in performing analytic tasks for ensemble data.

    Main Results:

    • Identified commonalities and differences in ensemble visualization techniques and their adaptations.
    • Highlighted how analytic tasks like comparison and clustering are addressed in ensemble data visualization.
    • Cataloged various visualization techniques applied to ensemble data, including surface and volume methods.

    Conclusions:

    • The survey offers a structured understanding of ensemble visualization's progress and current landscape.
    • Identified research trends and potential future directions for advancing ensemble data analysis and visualization.
    • A systematic overview is crucial for researchers to tackle unsolved problems and plan future research effectively.