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Somewhere Over the Rainbow: An Empirical Assessment of Quantitative Colormaps

Authors:

Jeffrey HeerAuthors Info & Claims

CHI '18: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems

Paper No.: 598, Pages 1 - 12

https://doi.org/10.1145/3173574.3174172

Published: 21 April 2018 Publication History

Abstract

An essential goal of quantitative color encoding is the accurate mapping of perceptual dimensions of color to the logical structure of data. Prior research identifies weaknesses of 'rainbow' colormaps and advocates for ramping in luminance, while recent work contributes multi-hue colormaps generated using perceptually-uniform color models. We contribute a comparative analysis of different colormap types, with a focus on comparing single- and multi-hue schemes. We present a suite of experiments in which subjects perform relative distance judgments among color triplets drawn systematically from each of four single-hue and five multi-hue colormaps. We characterize speed and accuracy across each colormap, and identify conditions that degrade performance. We also find that a combination of perceptual color space and color naming measures more accurately predict user performance than either alone, though the overall accuracy is poor. Based on these results, we distill recommendations on how to design more effective color encodings for scalar data.

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Cited By

Yan RSun JDavis A(2024)Chromaticity Gradient Mapping for Interactive Control of Color Contrast in Images and VideoProceedings of the 37th Annual ACM Symposium on User Interface Software and Technology10.1145/3654777.3676340(1-16)Online publication date: 13-Oct-2024
https://dl.acm.org/doi/10.1145/3654777.3676340
Hong MSunberg ZSzafir D(2024)Cieran: Designing Sequential Colormaps via In-Situ Active Preference LearningProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642903(1-15)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642903
McGee FMcCall RBaixauli J(2024)Comparison of Spatial Visualization Techniques for Radiation in Augmented RealityProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642646(1-15)Online publication date: 11-May-2024
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Index Terms

Somewhere Over the Rainbow: An Empirical Assessment of Quantitative Colormaps
1. Human-centered computing

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cover image ACM Conferences

CHI '18: Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems

April 2018

8489 pages

ISBN:9781450356206

DOI:10.1145/3173574

General Chairs:
Regan Mandryk
University of Saskatchewan, Canada
,
Mark Hancock
University of Waterloo, Canada
,
Program Chairs:
Mark Perry
Brunel University London, UK
,
Anna Cox
University College London, UK

Copyright © 2018 ACM.

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Published: 21 April 2018

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April 21 - 26, 2018

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Yan RSun JDavis A(2024)Chromaticity Gradient Mapping for Interactive Control of Color Contrast in Images and VideoProceedings of the 37th Annual ACM Symposium on User Interface Software and Technology10.1145/3654777.3676340(1-16)Online publication date: 13-Oct-2024
https://dl.acm.org/doi/10.1145/3654777.3676340
Hong MSunberg ZSzafir D(2024)Cieran: Designing Sequential Colormaps via In-Situ Active Preference LearningProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642903(1-15)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642903
McGee FMcCall RBaixauli J(2024)Comparison of Spatial Visualization Techniques for Radiation in Augmented RealityProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642646(1-15)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642646
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