Conveying Uncertainty in Data Visualizations to Screen-Reader Users Through Non-Visual Means Ather Sharif Ruican Zhong ∗ Yadi Wang ∗ asharif@cs.washington.edu rzhong98@uw.edu yadiw@cs.washington.edu Paul G. Allen School of Computer Human-Centered Design & Paul G. Allen School of Computer Science & Engineering | DUB Group, Engineering | DUB Group, Science & Engineering | DUB Group, University of Washington University of Washington University of Washington Seattle, Washington, USA Seattle, Washington, USA Seattle, Washington, USA Figure 1: A screen-reader user’s interaction with a data visualization of the average test scores for students. “Q” and “A” represent a question asked by a screen-reader user and the answer issued to them with and without enhancements to VoxLens, respectively. Error bars represent mean ±1 standard deviation. ABSTRACT Incorporating uncertainty in data visualizations is critical for users to interpret and reliably draw informed conclusions from the un- derlying data. However, visualization creators conventionally con- vey the information regarding uncertainty in data visualizations using visual techniques (e.g., error bars), which disenfranchises screen-reader users, who may be blind or have low vision. In this preliminary exploration, we investigated ways to convey uncer- tainty in data visualizations to screen-reader users. Specifcally, we conducted semi-structured interviews, fnding that these users prefer to obtain statistical information on uncertainty expressed in plain language, conveyed holistically with avenues to explore the ∗ These authors contributed equally to this work. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for proft or commercial advantage and that copies bear this notice and the full citation on the frst page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). ASSETS ’23, October 22–25, 2023, New York, NY, USA © 2023 Copyright held by the owner/author(s). ACM ISBN 979-8-4007-0220-4/23/10. https://doi.org/10.1145/3597638.3614502 data further in a drilled-down manner. To support screen-reader users in extracting information about uncertainty in online data visualizations, we utilized our fndings to enhance VoxLens—an open-source JavaScript plug-in that makes online data visualiza- tions accessible to screen-reader users. CCS CONCEPTS • Human-centered computing → Information visualization; Accessibility systems and tools;• Social and professional topics → People with disabilities. KEYWORDS uncertainty, visualizations, screen reader, blind, voxlens ACM Reference Format: Ather Sharif, Ruican Zhong, and Yadi Wang. 2023. Conveying Uncertainty in Data Visualizations to Screen-Reader Users Through Non-Visual Means. In The 25th International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS ’23), October 22–25, 2023, New York, NY, USA. ACM, New York, NY, USA, 6 pages. https://doi.org/10.1145/3597638.3614502