Visual Differentiation vs. Visual Grouping
Year: 2025
Type: article
Abstract: For business data visualization, there are two fundamental types of visual tasks: (a) differentiation tasks (identifying a data point or comparing individual data points) and (b) integration tasks (comparing sums of multiple data points and recognizing patterns). In this study, the authors propose a model of visual grouping that uses color to customize graphs for integration tasks. They conducted two experiments to investigate the effects of visual grouping on user performance across different task types. The results indicate that color grouping can enhance the outcomes of decision-making tasks, a specific type of integration task. More specifically, they found that when using graphs with visual grouping, participants spent significantly less time and achieved higher comprehension accuracy compared to those using graphs without visual grouping.
DOI: 10.4018/ijbir.380953
Authors: Fang Chen, Limin Zhang
Institutions: University of Montana, North Dakota State University
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4411410808