Modeling Color Difference for Visualization Design

Color is frequently used to encode values in visualizations. For color encodings to be effective, the mapping between colors and values must preserve important differences in the data. However, most guidelines for effective color choice in visualization are based on either color perceptions measured...

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Bibliographic Details
Published in:IEEE transactions on visualization and computer graphics Vol. 24; no. 1; pp. 392 - 401
Main Author: Szafir, Danielle Albers
Format: Journal Article
Language:English
Published: United States IEEE 01.01.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Bars
Color
Color Models
Color Perception
Computational modeling
Crowdsourcing
Data visualization
Design
Elongation
Encoding
Graphical Perception
Image color analysis
Measurement
Probabilistic models
Qualitative analysis
Visualization
ISSN:1077-2626, 1941-0506, 1941-0506
Online Access:Get full text
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Summary:Color is frequently used to encode values in visualizations. For color encodings to be effective, the mapping between colors and values must preserve important differences in the data. However, most guidelines for effective color choice in visualization are based on either color perceptions measured using large, uniform fields in optimal viewing environments or on qualitative intuitions. These limitations may cause data misinterpretation in visualizations, which frequently use small, elongated marks. Our goal is to develop quantitative metrics to help people use color more effectively in visualizations. We present a series of crowdsourced studies measuring color difference perceptions for three common mark types: points, bars, and lines. Our results indicate that peoples' abilities to perceive color differences varies significantly across mark types. Probabilistic models constructed from the resulting data can provide objective guidance for designers, allowing them to anticipate viewer perceptions in order to inform effective encoding design.
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ISSN:1077-2626
1941-0506
1941-0506
DOI:10.1109/TVCG.2017.2744359