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arxiv: 2604.09426 · v1 · submitted 2026-04-10 · 💻 cs.HC · cs.AI· cs.IR

Recognition: unknown

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

Sanchita S. Kamath , Aziz N Zeidieh , Venkatesh Potluri , Sile O'Modhrain , Kenneth Perry , JooYoung Seo
Authors on Pith no claims yet

Pith reviewed 2026-05-10 17:09 UTC · model grok-4.3

classification 💻 cs.HC cs.AIcs.IR
keywords accessibilityco-design3D visualizationsonificationblind and low-visionmulti-modal interfacesnon-visual dataSTEM accessibility
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The pith

An experience-based co-design process with blind and low-vision experts produced a multi-modal 3D data visualization prototype with audio features for analytic tasks.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper establishes that involving five BLV experts with non-visual data experience in two iterative sessions, comparing a tactile probe to a digital prototype, can ground the design of a web-native tool that combines audio and configurable data handling to explore 3D visualizations. This matters because 3D data like surface plots are essential in STEM fields such as biomedical imaging, yet inaccessible without vision, and the process translates tactile knowledge into digital interfaces that support tasks including orientation, peak finding, gradient tracing, and identifying occluded features. The co-designers validated that reference sonification, stereo and volumetric audio, and buffer aggregation improve accuracy and learnability. A sympathetic reader would care because it supplies a repeatable protocol and concrete feature guidance for making complex data usable by more people.

Core claim

Through Experience-Based Co-Design with five BLV co-designers in two sessions, the team created a prototype integrating reference sonification, stereo and volumetric audio, and configurable buffer aggregation. These features were validated as improving analytic accuracy and learnability for core non-visual tasks such as orientation, landmark and peak finding, comparing local maxima to global trends, gradient tracing, and identifying occluded features in 3D data.

What carries the argument

The Experience-Based Co-Design process that compares a low-fidelity tactile probe with a high-fidelity digital prototype across iterative sessions to derive multi-modal features from BLV expertise.

Load-bearing premise

Input from five BLV experts with prior non-visual representation skills across two short sessions is sufficient to establish that the audio and aggregation features will improve performance for the broader BLV population on real analytic tasks.

What would settle it

A follow-up study with additional BLV participants performing the listed analytic tasks on the prototype versus a version without the new audio features, showing no gains in accuracy or completion time, would challenge the claim.

Figures

Figures reproduced from arXiv: 2604.09426 by Aziz N Zeidieh, JooYoung Seo, Kenneth Perry, Sanchita S. Kamath, Sile O'Modhrain, Venkatesh Potluri.

Figure 1
Figure 1. Figure 1: Iterative Prototyping based on the EBCD Framework [PITH_FULL_IMAGE:figures/full_fig_p001_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: Experience-Based Co-Design: Research Timeline [PITH_FULL_IMAGE:figures/full_fig_p007_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: Low-Fidelity Prototype 4.2 High-Fidelity Design Probe Our high-fidelity design probe (created in Phase 2, Thrust 2 and employed in Phase 2 Thrust 3, Session 1 and 2) is a browser￾based, multi-modal platform that evolved directly from our auto￾ethnographic inquiry. To facilitate this, we made a deliberate method￾ological choice to build a modular system architecture. This archi￾tectural separation was the t… view at source ↗
Figure 4
Figure 4. Figure 4: Prototype interface though it was not implemented before Session 2. Thus, our final three design goals were formulated: DG3. The prototype should provide a reference point and replay mechanism to restore orientation during explo￾ration: Co-designers identified the fixed origin sonification and replay (.) as essential for regaining bearings after becom￾ing disoriented in complex data spaces. DG4. The protot… view at source ↗
Figure 5
Figure 5. Figure 5: AI Chat Interface [PITH_FULL_IMAGE:figures/full_fig_p023_5.png] view at source ↗
read the original 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.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

3 major / 2 minor

Summary. The paper reports on an experience-based co-design process involving five BLV co-designers (with prior non-visual data expertise) and one non-BLV researcher across two iterative sessions. A low-fidelity tactile probe was compared to a high-fidelity web-native digital prototype incorporating reference sonification, stereo/volumetric audio, and configurable buffer aggregation. The authors claim this yields empirically grounded features that co-designers validated as improving accuracy and learnability on core 3D analytic tasks (orientation, peak finding, gradient tracing, occluded feature identification), providing a co-design protocol and design guidance for accessible multi-modal 3D visualization.

Significance. If the validation claims hold, the work contributes a concrete co-design protocol for translating tactile knowledge into digital multi-modal interfaces and specific guidance on audio and aggregation features for 3D data tasks. This addresses an important accessibility gap in STEM visualization and could support future embodied data environments, with potential value for HCI and accessibility researchers seeking replicable methods.

major comments (3)
  1. Abstract: The central claim that the prototype features (reference sonification, stereo/volumetric audio, configurable buffer aggregation) were 'validated as improving analytic accuracy and learnability' rests exclusively on qualitative feedback from five expert co-designers in two short sessions. No quantitative metrics, task performance scores, baseline comparisons, error rates, or statistical details are reported, so the evidence does not yet support the empirical grounding asserted for the wider BLV population on real analytic tasks.
  2. Methods/Participants section: The co-designers were selected for prior expertise in non-visual representations; this introduces selection bias and limits generalizability. The manuscript should explicitly discuss how findings from this narrow, experienced cohort may or may not extend to naive BLV users, and whether additional validation with broader samples is planned.
  3. Results/Validation section: The distinction between co-design insights (useful for iteration) and performance validation (required for claims of improved accuracy/learnability) is not clearly drawn. Without controlled experiments, pre/post measures, or comparison to the tactile probe on scored tasks, the 'empirically grounded' language overstates what the qualitative sessions demonstrate.
minor comments (2)
  1. Prototype description: Provide more technical detail on implementation of 'volumetric audio' and 'configurable buffer aggregation' (e.g., exact audio parameters, web APIs used) to allow replication.
  2. Abstract and introduction: Ensure consistent terminology for modalities (tactile probe vs. digital audio) and clarify how the two sessions were structured (e.g., task order, duration).

Simulated Author's Rebuttal

3 responses · 0 unresolved

Thank you for the constructive feedback on our manuscript. We agree that the qualitative nature of the co-design study requires clearer framing to avoid overstating the scope of validation and generalizability. We will revise the abstract, methods, and results sections accordingly while preserving the core contributions of the experience-based protocol and design insights.

read point-by-point responses

  1. Referee: Abstract: The central claim that the prototype features (reference sonification, stereo/volumetric audio, configurable buffer aggregation) were 'validated as improving analytic accuracy and learnability' rests exclusively on qualitative feedback from five expert co-designers in two short sessions. No quantitative metrics, task performance scores, baseline comparisons, error rates, or statistical details are reported, so the evidence does not yet support the empirical grounding asserted for the wider BLV population on real analytic tasks.

    Authors: We agree that the abstract language overstates the findings. This is a qualitative experience-based co-design study, and 'validated' refers specifically to the iterative endorsements and reported improvements by the five expert co-designers in the sessions (e.g., their direct feedback on accuracy and learnability for tasks like peak finding). We make no quantitative or statistical claims for the wider population. We will revise the abstract to qualify these statements, remove 'empirically grounded' where it implies broader validation, and clarify the scope as co-designer-reported insights. revision: yes

  2. Referee: Methods/Participants section: The co-designers were selected for prior expertise in non-visual representations; this introduces selection bias and limits generalizability. The manuscript should explicitly discuss how findings from this narrow, experienced cohort may or may not extend to naive BLV users, and whether additional validation with broader samples is planned.

    Authors: We acknowledge the intentional selection of experienced co-designers for experience-based co-design, which introduces selection bias and limits generalizability. We will expand the Methods/Participants section to explicitly discuss these limitations, note that findings may not directly extend to naive BLV users without further testing, and state that additional validation with broader samples is planned in future work. revision: yes

  3. Referee: Results/Validation section: The distinction between co-design insights (useful for iteration) and performance validation (required for claims of improved accuracy/learnability) is not clearly drawn. Without controlled experiments, pre/post measures, or comparison to the tactile probe on scored tasks, the 'empirically grounded' language overstates what the qualitative sessions demonstrate.

    Authors: We agree the distinction is insufficiently clear. The results present co-design insights and participant feedback rather than controlled performance validation. We will revise the Results/Validation section to explicitly separate co-design insights from performance claims, remove or qualify 'empirically grounded' language, and emphasize that improvements in accuracy and learnability are based on qualitative reports from the sessions without controlled metrics or baselines. revision: yes

Circularity Check

0 steps flagged

No circularity: empirical co-design validation is self-contained

full rationale

The paper presents no derivation chain, equations, fitted parameters, or first-principles predictions. Its central claim—that specific audio and aggregation features improve analytic accuracy and learnability—rests directly on qualitative feedback collected during the described two-session co-design process with the five BLV participants. This feedback is treated as the source of the features rather than being redefined or predicted from prior author results. No self-citation load-bearing steps, uniqueness theorems, or ansatzes are invoked to justify the outcome; the methodology is an independent empirical protocol whose validity does not reduce to its own inputs by construction.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

The work rests on standard HCI domain assumptions about the value of co-design with domain experts rather than on mathematical derivations or new physical entities.

axioms (1)
  • domain assumption BLV users with expertise in non-visual representations can provide reliable guidance on effective multi-modal features for 3D data tasks
    Invoked to justify the choice of co-designers and the interpretation of their feedback as grounding the design.

pith-pipeline@v0.9.0 · 5561 in / 1329 out tokens · 46990 ms · 2026-05-10T17:09:18.963591+00:00 · methodology

discussion (0)

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Reference graph

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