Conference Paper

@inproceedings{chundury2024UnderstandingVisualization, title={Understanding the Visualization and Analytics Needs of Blind and Low-Vision Professionals}, author={Pramod Chundury and Urja Thakkar and Yasmin Reyazuddin and Jordan, J. Bern and Niklas Elmqvist and Jonathan Lazar}, url={https://doi.org/10.1145/3663548.3688496}, year={2024}, date={2024-01-28}, booktitle={Proceedings of the 26th International ACM SIGACCESS Conference on Computers and Accessibility}, publisher={Association for Computing Machinery}, address={New York, NY, USA}, pages={1--17}, doi={10.1145/3663548.3688496}, 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 fndings 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 feld of data science.}, series={ASSETS '24}, articleno={63}, numpages={17}, location={St. John's, NL, Canada}, language={English}, keywords={accessible data visualization,blind and low vision users,inclusive data analysis}, }