Using visualization requires people to read abstract visual imagery, estimate statistics and retain information. However, people with Intellectual and Developmental Disabilities (IDD) often process information differently, which may complicate connecting abstract visual information to real-world quantities. This population has traditionally been excluded from visualization design, and often has limited access to data related to their well being. We explore how visualizations may better serve this population. We identify three visualization design elements that may improve data accessibility: chart type, chart embellishment and data continuity. We evaluate these elements with populations both with and without IDDs, measuring accuracy and efficiency in a web-based online experiment with time series and proportion data. Our study identifies performance patterns and subjective preferences for people with possible solutions that may break the cognitive barriers caused by conventional design guidelines.
This is a collaborative project with University of Colorado's Coleman Institute for Cognitive Disabilities.
K. Wu, E. Petersen, T. Ahmad, D. Burlinson, E. S. Tanis, & D. Albers Szafir. 2021. Understanding Data Accessibility for People with Intellectual and Developmental Disabilities. (to appear) In Proceedings of the 2021 Conference on Human Factors in Computing Systems (CHI ‘21). (Yokohama, Japan–May 8-13, 2021) [Best Paper Award]. pdf. demo.
Additional Researcher: Emily Shea Tanis, director for policy and advocacy at the Coleman Institute for Cognitive Disabilities at the University of Colorado