Survey on Individual Differences in Visualization.
Published in Computer Graphics Forum, 2020
Abstract: Developments in data visualization research have enabled visualization systems to achieve great general usability and application across a variety of domains. These advancements have improved not only people’s understanding of data, but also the general understanding of people themselves, and how they interact with visualization systems. In particular, researchers have gradually come to recognize the deficiency of having one-size-fits-all visualization interfaces, as well as the significance of individual differences in the use of data visualization systems. Unfortunately, the absence of comprehensive surveys of the existing literature impedes the development of this research. In this paper, we review the research perspectives, as well as the personality traits and cognitive abilities, visualizations, tasks, and measures investigated in the existing literature. We aim to provide a detailed summary of existing scholarship, produce evidence-based reviews, and spur future inquiry.
Recommended citation: Zhengliang Liu, R. Jordan Crouser and Alvitta Ottley. Survey on individual differences in visualization. Computer Graphics Forum, 39(3): 693–712, 2020.