Survey on Individual Differences in Visualization
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Abstract (arXiv)
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.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). First posted on arXiv 19 Feb 2020.
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Citing papers per year: 2022: 1; 2023: 2; 2024: 1; 2025: 1.
5 papers.
- 2024Large Language Models for Robotics: Opportunities, Challenges, and Perspectivescited by 89
- 2023Towards Artificial General Intelligence (AGI) in the Internet of Things (IoT): Opportunities and Challengescited by 14
- 2023CLAMS: A Cluster Ambiguity Measure for Estimating Perceptual Variability in Visual Clusteringcited by 8
- 2025Tell Me Without Telling Me: Two-Way Prediction of Visualization Literacy and Visual Attentioncited by 1
- 2022A Unified Comparison of User Modeling Techniques for Predicting Data Interaction and Detecting Exploration Biascited by 0
- 2025Tell Me Without Telling Me: Two-Way Prediction of Visualization Literacy and Visual Attention22 Jul 2025
- 2024Large Language Models for Robotics: Opportunities, Challenges, and Perspectives9 Jan 2024
- 2023Towards Artificial General Intelligence (AGI) in the Internet of Things (IoT): Opportunities and Challenges14 Sep 2023
- 2023CLAMS: A Cluster Ambiguity Measure for Estimating Perceptual Variability in Visual Clustering1 Aug 2023
- 2022A Unified Comparison of User Modeling Techniques for Predicting Data Interaction and Detecting Exploration Bias9 Aug 2022