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    This review highlights underappreciated data management techniques for interactive visualization systems. Key areas like materialized views and approximate query processing offer significant potential for enhancing data analysis tools.

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    Area of Science:

    • Computer Science
    • Data Visualization
    • Data Management

    Background:

    • Interactive visualization and analysis are crucial for data-driven decisions.
    • Data management research offers technologies that enhance interactive analysis.

    Purpose of the Study:

    • To systematically review 30 years of data management work relevant to interactive visualization.
    • To identify and highlight underappreciated data management techniques for visualization.

    Main Methods:

    • Structured review along two axes: visualization task taxonomies and a data management categorization.
    • Characterized 131 research papers based on these axes.

    Main Results:

    • Identified five key data management concepts beneficial for interactive visualization: materialized views, approximate query processing, user modeling/query prediction, multi-query optimization, lineage, and indexing.
    • Found significant work in materialized views and approximate query processing, often targeting limited interaction tasks.

    Conclusions:

    • Data management techniques offer valuable, yet underutilized, opportunities for advancing interactive visualization.
    • Suggests future research directions at the intersection of data management and visualization, focusing on broader interaction task coverage.