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Related Experiment Video

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Mapping Color to Meaning in Colormap Data Visualizations.

Karen B Schloss, Connor C Gramazio, Allison T Silverman

IEEE Transactions on Visualization and Computer Graphics

|September 7, 2018

Summary

Background color significantly impacts how people interpret colormaps, influencing inferred color-quantity mappings. Understanding these biases, like dark-is-more and opaque-is-more, is key for effective data visualization design.

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Area of Science:

Human-Computer Interaction
Cognitive Psychology
Data Visualization

Background:

Interpreting data visualizations requires mapping visual features to concepts.
Colormap interpretation depends on how color dimensions map to quantities.
Matching visualizations to user's inferred mappings enhances understanding.

Purpose of the Study:

Investigate how background color influences inferred color-quantity mappings in colormaps.
Resolve conflicting prior research on background color effects.
Identify factors driving inferred mappings for better visualization design.

Main Methods:

Experimental study examining participant inferences of color-quantity relationships.
Manipulation of background color and colormap apparent opacity.
Analysis of inferred mappings based on participant responses.

Main Results:

Background color's effect on colormap interpretation depends on apparent opacity.
A 'dark-is-more' bias occurs when opacity is constant.
An 'opaque-is-more' bias emerges with increasing apparent opacity, potentially overriding 'dark-is-more'.

Conclusions:

Colormap interpretation is influenced by both inherent color properties and perceived opacity.
Design colormaps with consistent opacity and use darker colors for larger quantities for robust interpretation.
Avoid colormaps with apparent opacity variations to ensure consistent user perception across different backgrounds.