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  1. Home
  3. Reframing Pattern: A Comprehensive Approach To A Composite Visual Variable.
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  3. Reframing Pattern: A Comprehensive Approach To A Composite Visual Variable.

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Cross-Modal Multivariate Pattern Analysis
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Reframing Pattern: A Comprehensive Approach to a Composite Visual Variable.

Tingying He, Jason Dykes, Petra Isenberg

    IEEE Transactions on Visualization and Computer Graphics
    |November 21, 2025

    View abstract on PubMed

    Summary
    This summary is machine-generated.

    This study introduces a new theory for using patterns as a visual variable in data visualization. It provides a consistent framework for pattern design, enhancing its effective use in visual representations.

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    Area of Science:

    • Information Visualization
    • Human-Computer Interaction
    • Visual Analytics

    Background:

    • Patterns are crucial visual variables in data visualization but lack consistent theoretical foundations and terminology.
    • Inconsistent use of 'pattern' and 'texture' hinders effective application and research in visualization.

    Purpose of the Study:

    • To establish a comprehensive and consistent theory for pattern as a visual variable in visualization.
    • To clarify ambiguities in existing literature regarding the use of patterns and textures.
    • To formalize a new system for pattern design and explore its implications for visualization.

    Main Methods:

    • Conducted a comprehensive cross-disciplinary literature review to analyze existing concepts and terminology of patterns in visualization.
  • Developed a new theoretical framework defining patterns as composite visual variables made of structured graphic primitives.
  • Formalized a system for pattern design based on spatial arrangement, appearance relationships, and primitive visual variables.

    • Main Results:

    • Presented a novel, consistent treatment of pattern as a composite visual variable, clarifying its conceptual foundations.
    • Introduced a formal system for pattern design, expanding the design space for this visual variable.
    • Demonstrated the explanatory power of the proposed pattern system, particularly for complex spatial arrangements and cartographic theory.

    Conclusions:

    • The new theory provides a robust framework for understanding, designing, and utilizing patterns in data visualization.
    • This work bridges existing visualization theory with broader concepts, offering new opportunities for visualization design.
    • The formalized system facilitates more effective and research-informed application of patterns in visual representations.