Selecting Semantically-Resonant Colors for Data Visualization

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Date
2013
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association and Blackwell Publishing Ltd.
Abstract
We introduce an algorithm for automatic selection of semantically-resonant colors to represent data (e.g., using blue for data about ''oceans'', or pink for ''love''). Given a set of categorical values and a target color palette, our algorithm matches each data value with a unique color. Values are mapped to colors by collecting representative images, analyzing image color distributions to determine value-color affinity scores, and choosing an optimal assignment. Our affinity score balances the probability of a color with how well it discriminates among data values. A controlled study shows that expert-chosen semantically-resonant colors improve speed on chart reading tasks compared to a standard palette, and that our algorithm selects colors that lead to similar gains. A second study verifies that our algorithm effectively selects colors across a variety of data categories.
Description

        
@article{
:10.1111/cgf.12127
, journal = {Computer Graphics Forum}, title = {{
Selecting Semantically-Resonant Colors for Data Visualization
}}, author = {
Lin, Sharon
and
Fortuna, Julie
and
Kulkarni, Chinmay
and
Stone, Maureen
and
Heer, Jeffrey
}, year = {
2013
}, publisher = {
The Eurographics Association and Blackwell Publishing Ltd.
}, ISSN = {
1467-8659
}, DOI = {
/10.1111/cgf.12127
} }
Citation