The Accessibility of Data Visualizations on the Web for Screen Reader Users: Practices and Experiences During COVID-19

• Published in: ACM transactions on accessible computing 2023-03, Vol.16 (1), p.1-29, Article 4
• Main Authors: Fan, Danyang, Fay Siu, Alexa, Rao, Hrishikesh, Kim, Gene Sung-Ho, Vazquez, Xavier, Greco, Lucy, O'Modhrain, Sile, Follmer, Sean
• Format: Article
• Language: English
• Subjects: Empirical studies in accessibility; Human-centered computing; Visualization application domains
• ISSN: 1936-7228; 1936-7236
• DOI: 10.1145/3557899

Data visualization has become an increasingly important means of effective data communication and has played a vital role in broadcasting the progression of COVID-19. Accessible data representations, however, have lagged behind, leaving areas of information out of reach for many blind and visually impaired (BVI) users. In this work, we sought to understand (1) the accessibility of current implementations of visualizations on the web; (2) BVI users’ preferences and current experiences when accessing data-driven media; (3) how accessible data representations on the web address these users’ access needs and help them navigate, interpret, and gain insights from the data; and (4) the practical challenges that limit BVI users’ access and use of data representations. To answer these questions, we conducted a mixed-methods study consisting of an accessibility audit of 87 data visualizations on the web to identify accessibility issues, an online survey of 127 screen reader users to understand lived experiences and preferences, and a remote contextual inquiry with 12 of the survey respondents to observe how they navigate, interpret, and gain insights from accessible data representations. Our observations during this critical period of time provide an understanding of the widespread accessibility issues encountered across online data visualizations, the impact that data accessibility inequities have on the BVI community, the ways screen reader users sought access to data-driven information and made use of online visualizations to form insights, and the pressing need to make larger strides towards improving data literacy, building confidence, and enriching methods of access. Based on our findings, we provide recommendations for researchers and practitioners to broaden data accessibility on the web.