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 • Human-Computer Interaction
Human-Computer InteractionArtificial IntelligenceInformation Retrieval
AI summaryⓘ
The authors worked with blind and low-vision (BLV) experts to design a new tool that makes 3D data visualizations accessible without sight. They used feedback from different prototype versions to build features like audio cues and tactile controls that help users understand complex 3D data. Their tool helps BLV users complete important tasks such as finding key points and understanding shapes in the data. This study provides a process and design ideas for making future 3D visualizations easier for people who can't rely on vision.
3D data visualizationblind and low-vision (BLV)tactile probesonificationvolumetric audiointeractive prototypingmulti-modal interfacesdata accessibilityco-designorientation and landmark finding
Authors
Sanchita S. Kamath, Aziz N Zeidieh, Venkatesh Potluri, Sile O'Modhrain, Kenneth Perry, JooYoung Seo
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.