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Three-layer reusable pipeline for generating 3D-printed tactile statistical graphs

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Evidence · 2 claims (2 for) · 1 study (1 design), q2 · 0 of 1 report an effect size · 2 claims rest on one study

Description

An open-source JavaScript pipeline by Lawrence Obiuwevwi et al. that generates 3D-printable tactile statistical graphs from typed data or chart images for blind and low-vision statistics learners.

Components

  • Derive tactile graph parameters from tactile perception research rather than ad hoc choices: The pipeline's parameter derivation layer computes feature heights and spacings automatically from plate dimensions using established tactile perception findings, so every generated chart is readable by touch without per-chart manual tuning. Data features are set at 1.5 mm, three times the "0.5 mm height discriminability floor" from Lederman and Klatzky, and scatter-point separation is 3.5 mm, exceeding the 2–3 mm two-point discrimination threshold. Axis rails are taller than data features so a sweeping finger distinguishes structural boundaries from encoded data. (Lawrence Obiuwevwi et al. (2026))

Claims

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Key Sources

  • Lawrence Obiuwevwi, Krzysztof J. Rechowicz, Jessica M. Johnson, Erika Frydenlund, Vikas Ashok, Sachin Shetty, & Sampath Jayarathna. (2026). Touching and Feeling the Data: A Reusable Software Pipeline for Tactile Statistical Graphs in Accessible Education. arXiv. https://arxiv.org/abs/2607.01214
Page metadata
Field Value
type product
id three-layer-reusable-pipeline-for-generating-3d-printed-tactile-statistical-graphs
title Three-layer reusable pipeline for generating 3D-printed tactile statistical graphs
description An open-source JavaScript pipeline by Lawrence Obiuwevwi et al.
status review
product_kind software
generated by process:settle-candidates on 2026-10-11
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