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.

翻译：三维（3D）数据可视化（如曲面图）在生物医学成像到光谱学等STEM领域至关重要，但对盲人和低视力（BLV）群体而言仍基本不可及。为填补这一空白，我们与具有非视觉数据表征专业知识的BLV协同设计师开展了基于经验的协同设计，旨在创建可访问的多模态网页原生可视化工具。采用多阶段方法，由五位BLV研究员与一位非BLV研究员组成的团队参与了两轮迭代实验，对比了低保真触觉探针与高保真数字原型。该过程产出一个具有经验验证特征的原型，包括参考声化、立体与体积音频、可配置缓冲区聚合等——这些特征经协同设计师验证可提升分析准确性与可学性。本研究聚焦非视觉三维数据探索的核心分析任务：定向导航、标志点与峰值识别、局部极值与全局趋势比较、梯度追踪，以及遮挡或部分隐藏特征的辨识。我们的工作为无障碍研究人员与开发者提供了将触觉知识转化为数字界面的协同设计方案、未来系统的具体设计指导，以及将无障碍三维可视化延伸至具身数据环境的可能路径。