Enabling Tabular Data Exploration for Blind and Low-Vision Users

In a data-driven society, being able to examine data on one's own terms is crucial for various aspects of well-being. However, current data exploration paradigms, such as Exploratory Data Analysis (EDA), heavily rely on visualizations to unveil patterns and insights. This visual-centric approach poses significant challenges for blind and low-vision (BLV) individuals. To address this gap, we built a prototype that supports non-visual data exploration and conducted an observational user study involving 18 BLV participants. Participants were asked to conduct various analytical tasks, as well as free exploration of provided datasets. The study findings provide insights into the factors influencing inefficient data exploration and characterizations of BLV participants' analytical behaviors. We conclude by highlighting future avenues of research for the design of data exploration tools for BLV users.