Our paper, “Affective color scales for colormap data visualizations,” was published in IEEE Transactions on Visualization and Computer Graphics.
AUthors: Halle c. braun, kushin mukherjee, seth r. gorelik, & Karen b. Schloss
Research on affective visualization design has shown that color is an especially powerful feature for influencing the emotional connotation of visualizations. Associations between colors and emotions are largely driven by lightness (e.g., lighter colors are associated with positive emotions, whereas darker colors are associated with negative emotions). Designing visualizations to have all light or all dark colors to convey particular emotions may work well for visualizations in which colors represent categories and spatial channels encode data values. However, this approach poses a problem for visualizations that use color to represent spatial patterns in data (e.g., colormap data visualizations) because lightness contrast is needed to reveal fine details in spatial structure. In this study, we found it is possible to design colormaps that have strong lightness contrast to support spatial vision while communicating clear affective connotation. We also found that affective connotation depended not only on the color scales used to construct the colormaps, but also the frequency with which colors appeared in the map, as determined by the underlying dataset (data-dependence hypothesis). These
results emphasize the importance of data-aware design, which accounts for not only the design features that encode data (e.g., colors, shapes, textures), but also how those design features are instantiated in a visualization, given the properties of the data.
Reference: Braun, H. C., Mukherjee, K., Gorelik, S. R., & Schloss, K. B (2026). Affective color scales for colormap data visualizations. IEEE Transactions on Visualization and Computer Graphics, 32, 1, 692-702. Honorable mention for Best Paper at IEEE VIS 2025. PDF
Studies of visual semantics for information visualization aim to understand observers’ expectations about the meaning of visual features (e.g., color, texture) because visualizations that align with those expectations are easier to interpret. Previous work on visual semantics focused primarily on color, with the implicit assumption that color semantics is unaffected by changes in the size of the visualization (given sufficient perceptual discriminability across sizes). Changing size from small scale (e.g., small figures in a paper) to large scale (e.g., large figures in a slide presentation) is straightforward for visualizations that have solid colored regions, but can be more complicated for visualizations with heterogeneous textures because there are multiple ways to scale textures—zooming or repeating texture elements. Previous work suggested that original textures were more perceptually similar to repeat-scaled rather than zoom-scaled textures. Here, we found that texture semantics was preserved after both types of enlargement, suggesting that texture semantics is robust to scaling, at least for geometric textures in which elements are visible at all scales.
Dr. Melissa Schoenlein defended her dissertation on Effects of color category structure on learning and generalization of color-concept associations for novel concepts. Now, Melissa is off to start a faculty position in Psychology at High Point University!
Melissa Schoenlein was awarded a 2023-2024 UW-Madison Capstone Teaching Award for her course Psychology of Information Visualization (Spring 2023)! This award recognizes dissertators at the end of their graduate program with an outstanding teaching record over the course of their UW–Madison tenure.
PI Karen Schloss received the 2023 Department Teaching Award for important contributions in teaching from the UW-Madison Department of Psychology.
Congratulations to Zoe Howard and Melina Mueller for receiving an Outstanding Undergraduate Research Scholar (OURS) Award. This award recognizes outstanding undergraduate Psychology majors for their contribution to research in our department. We thank Zoe and Melina for their outstanding work in our lab!
Congratulations to Melina Mueller for receiving a Hilldale Undergraduate/Faculty Research Fellowship, which provides research training and support for undergraduates to undertake their own research project in collaboration with UW–Madison faculty or research/instructional academic staff. This award will support Melina’s honors thesis project investigating the effects of verbal interference on color category extrapolation for learning novel color-concept associations (advised by PI Karen Schloss and graduate student Melissa Schoenlein).