Lost in Magnitudes: Exploring Visualization Designs for Large Value Ranges

要旨

We explore the design of visualizations for values spanning multiple orders of magnitude; we call them Orders of Magnitude Values (OMVs). Visualization researchers have shown that separating OMVs into two components, the mantissa and the exponent, and encoding them separately overcomes limitations of linear and logarithmic scales. However, only a small number of such visualizations have been tested, and the design guidelines for visualizing the mantissa and exponent separately remain under-explored. To initiate this exploration, better understand the factors influencing the effectiveness of these visualizations, and create guidelines, we adopt a multi-stage workflow. We introduce a design space for visualizing mantissa and exponent, systematically generating and qualitatively evaluating all possible visualizations within it. From this evaluation, we derive guidelines. We select two visualizations that align with our guidelines and test them using a crowdsourcing experiment, showing they facilitate quantitative comparisons and increase confidence in interpretation compared to the state-of-the-art.

受賞
Best Paper
著者
Katerina Batziakoudi
Berger-Levrault, Boulogne-Billancourt, France
Florent Cabric
Aviz, Inria, Saclay, France
Stéphanie Rey
Berger-Levrault, Toulouse, France
Jean-Daniel Fekete
Inria, Saclay, France
DOI

10.1145/3706598.3713487

論文URL

https://dl.acm.org/doi/10.1145/3706598.3713487

動画

会議: CHI 2025

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)

セッション: Visualization

G302
7 件の発表
2025-04-29 01:20:00
2025-04-29 02:50:00
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