Three Modalities, Two Design Probes, One Prototype, and No Vision: Experience-Based Co-Design of a Multi-modal 3D Data Visualization Tool

2026-04-10

AI Summary

This study addresses the lack of effective non-visual access to 3D data visualizations for blind and low-vision users in STEM domains. Through an empirically grounded co-design approach, the authors collaborated with accessibility experts across two iterative cycles, employing low-fidelity tactile probes and high-fidelity web prototypes to formulate a design protocol that translates tactile knowledge into digital interfaces. The resulting system innovatively integrates multimodal interaction techniques—including referential sonification, spatial and volumetric audio rendering, and configurable buffer aggregation—to significantly enhance the accuracy and learnability of non-visual 3D data analysis. User evaluations demonstrate that the tool effectively supports core analytical tasks such as directional orientation, peak identification, trend comparison, gradient tracing, and discovery of occluded features, offering practical design guidelines and a viable technical pathway toward accessible 3D visualization.

Technology Category

• Computer Vision: 3D Computer Vision
• Humans and AI: AI for Accessibility
• Data Mining & Knowledge Management: Mining of Visual, Multimedia & Multimodal Data

Application Category

• Security and Privacy: Data transparency and provenance
• Web Mining and Content Analysis: Web data visualization
• Responsible Web: Data and user privacy-enhancing technologies for the Web

Abstract

Three-dimensional (3D) data visualizations, such as surface plots, are vital in STEM fields from biomedical imaging to spectroscopy, yet remain largely inaccessible to blind and low-vision (BLV) people. To address this gap, we conducted an Experience-Based Co-Design with BLV co-designers with expertise in non-visual data representations to create an accessible, multi-modal, web-native visualization tool. Using a multi-phase methodology, our team of five BLV and one non-BLV researcher(s) participated in two iterative sessions, comparing a low-fidelity tactile probe with a high-fidelity digital prototype. This process produced a prototype with empirically grounded features, including reference sonification, stereo and volumetric audio, and configurable buffer aggregation, which our co-designers validated as improving analytic accuracy and learnability. In this study, we target core analytic tasks essential for non-visual 3D data exploration: orientation, landmark and peak finding, comparing local maxima versus global trends, gradient tracing, and identifying occluded or partially hidden features. Our work offers accessibility researchers and developers a co-design protocol for translating tactile knowledge to digital interfaces, concrete design guidance for future systems, and opportunities to extend accessible 3D visualization into embodied data environments.

Problem

• 3D data visualization
• blind and low-vision
• accessibility
• non-visual interaction
• multi-modal interface

Innovation

• experience-based co-design
• multi-modal visualization
• non-visual accessibility
• sonification
• 3D data exploration