Taxonomy-Based Glyph Design—with a Case Study on Visualizing Workflows of Biological Experiments

Area of Science:

• Information Visualization
• Bioinformatics
• Human-Computer Interaction

Background:

• Glyph design is often intuitive, limiting scalability for complex data.
• Visualizing multivariate information requires efficient and effective methods.
• Biological experiment workflows present a significant visualization challenge.

Purpose of the Study:

• To propose a systematic, scalable process for glyph design.
• To align concept hierarchy with visual channel discriminability.
• To develop effective glyphs for visualizing biological experiment workflows.

Main Methods:

• Explored the parallel between concept categorization hierarchy and visual channel discriminability.
• Developed a computational approach for formulating taxonomies.
• Defined application-specific abstractions and metaphors for glyph encoding.

Main Results:

• Demonstrated a cost-effective glyph design process.
• Successfully applied the method to visualize thousands of biological workflow records.
• Showcased enhanced efficiency and effectiveness in visual search for complex data.

Conclusions:

• A systematic glyph design process enhances multivariate data visualization.
• Computational taxonomy formulation and hierarchical visual channel selection are key.
• The proposed method offers a scalable solution for complex biological data representation.