A Design Space for Visualizations with Large Differences Between Largest and Smallest Elements

Designers have developed many approaches to overcome the challenge of designing visualizations where the smallest data items can be clearly seen from a high level. This paper presents a design space for visualization with large scale-item ratios, which includes three dimensions and eight subdimensions. The authors demonstrate the descriptive and generative power of the design space by using it to code a corpus of 54 examples and identify missed opportunities within the corpus.