Effect of color properties in multiple time series graph comprehension

Abstract

Multiple time series graphs are used prevalently in representing business and research data, but the use of color properties to visualize them to enhance comprehension is limited. This study explored the effect of hue and lightness in representing 4-time series data in relation to response time (RT) and accuracy. Two types of palettes were developed for each experiment: monochrome and multi-hue. The three sets of monochrome palettes created were red, green, and blue, while four equidistant hues in the color wheel were used in the multi-hue palette: red, blue, green, and purple. A total of forty people participated in the two experiments. Participants performed two tasks for both experiments: maximum and discrimination tasks. The monochrome experiment showed the primacy of green in terms of RT and accuracy in the discrimination task. RT and accuracy were significantly affected by lightness in the multi-hue experiment. For both tasks, RT was longer for 20% lightness and lowest at 60% lightness. Accuracy results were also consistent with RT. In the discrimination task, participants made more errors in 20% lightness and the highest accuracy for 60% and 80%.

Keywords: Color; Data and knowledge visualization; Graphics recognition and interpretation; Time series analysis.