Shakila Cherise S. Joyner
Boston College, Boston , Massachusetts, United States
Data visualizations are now widely used across many disciplines. However, many of them are not easily accessible for visually impaired people. In this work, we use three-staged mixed methods to understand the current practice of accessible visualization design for visually impaired people. We analyzed 95 visualizations from various venues to inspect how they are made inaccessible. To understand the rationale and context behind the design choices, we also conducted surveys with 144 practitioners in the U.S. and follow-up interviews with ten selected survey participants. Our findings include the difficulties of handling modern complex and interactive visualizations and the lack of accessibility support from visualization tools in addition to personal and organizational factors making it challenging to perform accessible design practices.
https://dl.acm.org/doi/abs/10.1145/3491102.3517630
The ACM CHI Conference on Human Factors in Computing Systems (https://chi2022.acm.org/)