Understanding the Visualization and Analytics Needs of Blind and Low-Vision Professionals

Inclusivity for blind and low vision (BLV) professionals in data science and analytics is limited by a gap in understanding their unique data analysis needs. We contribute to the literature by reporting on a two-step online survey delving into the experiences and challenges faced by BLV individuals engaged in data-related roles. Our findings highlight that despite expertise in programming and GUI-based analysis tools, BLV professionals faced accessibility issues at various points in the data analysis pipeline—issues ranging from data loading and transformation, availability and compatibility of data tools with assistive technology, and visualization authoring. The prevalent use of tools such as Excel, Python, and SAS alongside heavy reliance on assistive technologies highlights persistent accessibility challenges. Furthermore, frequent collaboration with sighted colleagues indicates compromised independence. These results underscore the urgent need for “born accessible” tools that ensure the inclusivity and autonomy of BLV professionals in the field of data science.

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Publication Details

Published
2024-10-20
DOI
https://doi.org/10.1145/3663548.3688496
Citations
4
Primary Topic
Data Visualization and Analytics
Type
article
Field-Weighted Citation Impact
1.00
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article

Understanding the Visualization and Analytics Needs of Blind and Low-Vision Professionals

Umesh Thakkar, Jonathan Lazar, Yasmin Reyazuddin, Niklas Elmqvist et al.
4 citations
Data Visualization and Analytics
1.00
article

Understanding the Visualization and Analytics Needs of Blind and Low-Vision Professionals

Umesh Thakkar, Jonathan Lazar, Yasmin Reyazuddin, Niklas Elmqvist, J. Bern Jordan, Pramod Chundury
article en
4 citations

Abstract

Inclusivity for blind and low vision (BLV) professionals in data science and analytics is limited by a gap in understanding their unique data analysis needs. We contribute to the literature by reporting on a two-step online survey delving into the experiences and challenges faced by BLV individuals engaged in data-related roles. Our findings highlight that despite expertise in programming and GUI-based analysis tools, BLV professionals faced accessibility issues at various points in the data analysis pipeline—issues ranging from data loading and transformation, availability and compatibility of data tools with assistive technology, and visualization authoring. The prevalent use of tools such as Excel, Python, and SAS alongside heavy reliance on assistive technologies highlights persistent accessibility challenges. Furthermore, frequent collaboration with sighted colleagues indicates compromised independence. These results underscore the urgent need for “born accessible” tools that ensure the inclusivity and autonomy of BLV professionals in the field of data science.

National Federation of the Blind (US), Aarhus University (DK), University of Maryland, College Park (US)
Quality Education
Openalex Percentile: Top 22%
Data Visualization and Analytics
1.00
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