Core Concepts
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.
Abstract
The paper presents a design space for visualization with large scale-item ratios, which is the relationship between the largest scale and the smallest item in a visualization. Designing visualizations in this context can be challenging, as the smallest items may not be visible or clearly separable.
The design space includes three main dimensions:
Scales: This dimension describes the number of scales, how the scales differ in mapping, whether they share encodings, and how they are associated.
Navigation: This dimension covers the interaction capabilities, including the type of navigation (zooming, panning, or both), the mode (physical or digital), and whether it relies on visceral time.
Familiarity: This dimension describes whether the visualization compares unfamiliar objects to familiar ones to help users understand the scale.
The authors demonstrate the descriptive power of the design space by using it to code a corpus of 54 examples, both from academic literature and practitioner work. They also identify five strategies that partition the examples based on shared approaches for design space choices.
The authors further demonstrate the generative power of the design space by analyzing missed opportunities within the corpus, where different design space choices could have improved the visualizations. For example, they suggest that some examples could have benefited from using physical navigation, employing more simultaneous and separate scales, using different encodings on different scales, or incorporating visceral time and familiarity.
Overall, the design space provides a structured framework for reasoning about and generating visualizations with large scale-item ratios.
Stats
The scale-item ratio is the ratio between the size of the largest scale and the size of the smallest item, both in display space.
The authors define value as the magnitude of data items in data space, and a mapping as a transformation from a value to a discretized display space position.
A scale is a region of the discretized display space that depicts a mapping, and it ranges from minimum to maximum positions in display space.
A size is the difference between a scale or an item's minimum and maximum positions in display space.
Quotes
"The scale-item ratio is the relationship between the largest scale and the smallest item in a visualization. Designing visualizations when this ratio is large can be challenging, and designers have developed many approaches to overcome this challenge."
"We present a design space for visualization with large scale-item ratios. The design space includes three dimensions, with eight total subdimensions."