An extension of Wilkinson's algorithm for positioning tick labels on axes

Area of Science:

• Information Visualization
• Computer Graphics
• Human-Computer Interaction

Background:

• Non-data visualization components like axes and legends are crucial for data interpretation.
• Existing automated labeling approaches have limitations in handling complex cases and optimizing multiple visual attributes.

Purpose of the Study:

• To develop a more robust and full-featured automated system for axis tick mark labeling.
• To enhance the quality and legibility of axis labels in information visualizations.

Main Methods:

• Extending Wilkinson's optimization-based labeling approach.
• Generating additional 'nice' numbers and allowing extreme labels within the data range.
• Introducing 'legibility' as an optimization criterion, considering label formatting, font size, and orientation.

Main Results:

• The proposed system offers greater flexibility in problematic labeling scenarios without compromising quality.
• Simultaneous optimization of label placement, formatting, font size, and orientation is achieved.
• The method demonstrates superior performance compared to previous work based on quantitative and qualitative metrics.

Conclusions:

• Automated graphic design principles can be effectively applied to enhance information visualization.
• The developed axis labeler provides a more robust and flexible solution for creating informative visualizations.