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    Area of Science:

    • Information Visualization
    • Human-Computer Interaction
    • Data Analysis

    Background:

    • Complex data analysis often necessitates coordinating multiple visualizations (views).
    • Current tools rely on brushing and linking, which can be effort-intensive for exploring cross-view relationships.
    • Lack of design guidelines hinders effective visualization of multi-view data relationships.

    Purpose of the Study:

    • To present systematic design considerations for visualizing cross-view data relationships.
    • To leverage descriptive aspects of relationships and visual context in multi-view visualizations.
    • To provide recommendations for practitioners to improve multi-view data analysis.

    Main Methods:

    • Systematic design considerations for visualizing cross-view data relationships.
    • Leveraging descriptive aspects of relationships and usable visual context.
    • Discussion of pros and cons of different design approaches.

    Main Results:

    • Identified key design considerations for visualizing cross-view data relationships.
    • Evaluated various methods for displaying relationships between multiple views.
    • Provided a framework for making informed design decisions in multi-view visualization.

    Conclusions:

    • Effective visualization of cross-view relationships can significantly enhance data analysis.
    • Design choices impact the usability and efficiency of exploring multi-view data.
    • Recommendations are provided to guide practitioners in designing better multi-view visualization systems.