AutoVizuA11y: A tool to automate accessibility in data visualizations for screen reader users

Abstract

Data visualizations remain widely inaccessible for screen reader users on the web. Despite recent research, developers still lack the experience, knowledge, and time to consistently implement accessible features. As a result, screen reader users lose access to information and are compelled to resort to tabular alternatives, when available, limiting their access to information. These issues make it impossible for users of screen readers to work in areas like financial fraud detection and demand the exploration of data through different chart types. We worked with screen reader users and chart creators at Feedzai to develop AutoVizuA11y, a tool that automates the addition of accessible features to web-based charts. It enables keyboard navigation, offers shortcuts for faster exploration, provides automatic labeling, and generates human-like descriptions of the data using a large language model. Through a series of task-based tests (16 tasks and 15 users) comparing two interfaces — one with AutoVizuA11y charts resembling Feedzai’s environment and the other with accessible tables — we show that with AutoVizuA11y users are, on average, faster (66 vs 78 seconds) and more accurate (89% vs 79% accuracy).