This study builds on past research bridging spatial visualization, psychology, and information visualization to holistically inform visualization design. We investigate the effects of chosen disciplines in psychology and math & computer science, combined with cognitive abilities and demographic differences, on visual tasks by measuring estimation of Pearson's correlation coefficient in scatterplots. Results reveal mathematicians demonstrate greater accuracy, benefiting from domain expertise. However, psychologists with high spatial skills outperform some mathematicians with lower spatial skills. Spatial visualization, level of education, and age (inversely) correlated with quicker and more accurate responses. Findings prove that domain expertise and spatial cognition affect correlation judgments in scatterplots, supporting that individual differences should inform visualization design. This work introduces psychologists as a new target domain for visualization research and reveals the impact of combined effects of cognitive abilities and domain on the estimation and manipulation of Pearson's correlation coefficient.

This study builds on past research to present a domain-specific empirical investigation of artists and math & computer scientists on their respective relationships to, perceptions of, and interactions with data visualization. We conducted a three-phase study utilizing mixed-methods to investigate performance on visual and text representations of data between domains. Our findings evidenced how math & computer scientists are proficient utilizing text representations of data while artists benefit more from visual chart representations. Finally, we present perspectives from artists to gain an understanding of their approach to visual and mathematical tasks. Our findings indicate that artists are especially adept at statistical visual tasks and that development of cognitive skills could be fostered by individuals to potentially benefit visualization task performance.

Understanding one's audience is foundational to creating high impact visualization designs. However, individual differences and cognitive abilities influence interactions with information visualization. Different user needs and abilities suggest that an individual's background could influence cognitive performance and interactions with visuals in a systematic way. This study builds on current research in domain-specific visualization and cognition to address if domain and spatial visualization ability combine to affect performance on information visualization tasks. We measure spatial visualization and visual task performance between those with tertiary education and professional profile in business, law & political science, and math & computer science. We conducted an online study with 90 participants using an established psychometric test to assess spatial visualization ability, and bar chart layouts rotated along Cartesian and polar coordinates to assess performance on spatially rotated data. Accuracy and response times varied with domain across chart types and task difficulty. We found that accuracy and time correlate with spatial visualization level, and education in math & computer science can indicate higher spatial visualization. Additionally, we found that motivational differences between domains could contribute to increased levels of accuracy. Our findings indicate discipline not only affects user needs and interactions with data visualization, but also cognitive traits. Our results can advance inclusive practices in visualization design and add to knowledge in domain-specific visual research that can empower designers across disciplines to create effective visualizations.