Studying Color Blending Perception for Data Visualization

Abstract

Visualization is a powerful way to convey data, showing a great potential for joining and interrelating differentdata items. Nevertheless, when dealing with large amounts of data, visually merging different classes of informationposes several challenges. Color, however, due to its effectiveness for labeling and categorizing information,may be a solution to this shortcoming. Merging items with different colors may suggest mixing their original colors.This approach, while generating an immediately perceivable way to represent merged items, keeps contextthrough the association of the resulting color to its original provenience. We studied to which extent color blendingprovides users with the means to understand the provenience of data items by conducting a user study with73 subjects using CIE-LCh blending to ascertain (i) to which extent people are able to, given a particular color,understand its provenience, and (ii) the color model in which to perform color blending so that users find blendingintuitive. Results showed that people have difficulties in understanding blending of colors that are farther apart inthe color wheel and indicated that the CMYK model may show promise for representing blended colors.