Color Quest: an interactive tool for exploring color palettes and enhancing accessibility in data visualization

Nelli, L. (2024) Color Quest: an interactive tool for exploring color palettes and enhancing accessibility in data visualization. PLoS ONE, 19(3), e0290923. (doi: 10.1371/journal.pone.0290923) (PMID:38502671) (PMCID:PMC10950247)

Abstract

Data visualization plays a vital role in modern scientific communication across diverse domains, shaping the understanding of complex information through color choices. However, the significance of color palette selection goes beyond aesthetics and scientific communication, encompassing accessibility for all, especially individuals with color vision deficiencies. To address this challenge, we introduce "Color Quest," an intuitive Shiny app that empowers users to explore color palettes for data visualization while considering inclusivity. The app allows users to visualize palettes across various types of plots and maps envisioning how they appear to individuals with color blindness. In addition, it enables users to visualize palettes on their own custom-uploaded images. This short communication presents the app’s design, interactive interface, and transformative potential in enhancing data visualization practices. Developed using open-source standards, Color Quest aligns with accessibility discussions, offering a practical tool and platform for raising awareness about inclusive design. Its open-source nature fosters transparency, community collaboration, and long-term sustainability. Color Quest’s practicality renders it indispensable for scientific domains, simplifying palette selection and promoting accessibility. Its impact extends beyond academia to diverse communication settings, harmonizing information dissemination, aesthetics and accessibility for more impactful scientific communication.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Nelli, Dr Luca

Creator Roles

Nelli, L.: Conceptualization, Data curation, Formal analysis, Methodology, Software, Visualization, Writing – original draft

• Authors: Nelli, L.
• College/School: College of Medical Veterinary and Life Sciences > School of Biodiversity, One Health & Veterinary Medicine
• Journal Name: PLoS ONE
• Publisher: Public Library of Science
• ISSN: 1932-6203
• ISSN (Online): 1932-6203
• Copyright Holders: Copyright © 2024 Luca Nelli
• First Published: First published in PLoS ONE 19(3):e0290923
• Publisher Policy: Reproduced under a Creative Commons license