Understanding and Improving Drilled-Down Information Extraction from Online Data Visualizations for Screen-Reader Users

Inaccessible online data visualizations can significantly disenfranchise screen-reader users from accessing critical online information. Current accessibility measures, such as adding alternative text to visualizations, only provide a high-level overview of data, limiting screen-reader users from exploring data visualizations in depth. In this work, we developed taxonomies of information sought by screen-reader users to interact with online data visualizations granularly through role-based and longitudinal studies with screen-reader users. Utilizing these taxonomies, we extended the functionality of VOXLENS by supporting drilled-down information extraction. We assessed the performance of our VOXLENS enhancements through task-based user studies.