A Design Space for Multiscale Visualization

Area of Science:

• Information Visualization
• Human-Computer Interaction
• Data Science

Background:

• Designing visualizations with large scale ratios presents significant challenges.
• Numerous approaches exist to address multiscale visualization design.
• A structured framework is needed to understand and develop these approaches.

Purpose of the Study:

• To introduce a novel design space for multiscale visualization.
• To analyze and categorize existing multiscale visualization design approaches.
• To identify opportunities for improving multiscale visualization design.

Main Methods:

• Developed a design space with three dimensions and eight subdimensions.
• Coded 52 examples of multiscale visualizations using the design space.
• Analyzed examples to identify high-level design strategies and patterns.
• Examined missed opportunities within the example corpus.

Main Results:

• The design space effectively describes existing multiscale visualization approaches.
• Identified four high-level strategies for designing multiscale visualizations.
• Revealed patterns in design choices across analysis and presentation contexts.
• Highlighted areas for potential design improvements.

Conclusions:

• The proposed design space provides a valuable framework for understanding multiscale visualization design.
• The identified strategies offer guidance for practitioners and researchers.
• Further exploration of design space dimensions can lead to innovative visualization techniques.