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. 2024 Mar 19;19(3):e0290923. doi: 10.1371/journal.pone.0290923

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

Luca Nelli 1,*
Editor: Mohamed Rafik N Qureshi2
PMCID: PMC10950247  PMID: 38502671

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.

Introduction

Data visualization stands as an indispensable medium for conveying intricate information, serving as a cornerstone of modern communication across diverse domains [1]. The selection of colors within plots, graphs and maps, once viewed primarily through an aesthetic lens, has taken on a new dimension—one that encapsulates the nuances of accessibility, ethical considerations, and universal comprehension. This significance gains further weight when considering the prevalence of color vision deficiencies that impact a substantial portion of the population [2, 3]. The complications arising from certain color selections, such as the rainbow or jet color map, can inadvertently misrepresent data, with those affected by color vision deficiencies often bearing the unintended repercussions of such choices in scientific communication [4, 5], which, in turn, highlights the critical need for innovative solutions to bridge this comprehension gap.

Recently, Stoelzle and Stein [6] undertook a meticulous review of color usage across scientific papers. Their analysis revealed that approximately that approximately 47% of publications in Hydrology and Earth System Sciences (HESS) in 2020 used visualizations that were not scientifically correct, perceptually uniform, and challenging for readers with color vision deficiencies. This trend seems persistent, as almost half of the 800 papers surveyed from 2005 to 2020 across the journal exhibited issues with ambiguous or non-colorblind-friendly color maps. Intriguingly, these tendencies were not confined to one journal; a similar survey in renowned journals such as Nature Scientific Reports and Nature Communications indicated that a significant proportion of papers across diverse disciplines also fell into the same trap. The authors speculate that this prevalence could be linked to a rise in spatial analyses or cartographic maps in research, often leading to misleading visualizations.

Given this prevalent challenge, an ethical imperative therefore emerges, especially in light of color vision deficiencies affecting a significant portion of the population [2, 3]. Achieving a harmonious equilibrium between visual allure and inclusivity is the crux of this endeavor [7].

Inspired by the call for accessibility considerations in color choices (e.g. [7–11]), I introduce "Color Quest", an intuitive Shiny app designed to aid users in creating accessible and visually appealing color palettes for data visualization. Color Quest offers users the ability to envision their chosen color palettes from the perspective of individuals with color blindness, by simulating scatter plots, line plots, box plots, histograms, and heatmaps. In addition, it enables users to upload their existing images and plots, providing simulations of how these visuals would appear to individuals with color vision deficiencies.

By addressing issues related to color accessibility, misuse, and inclusivity, "Color Quest" contributes to improving the overall quality and impact of scientific communication through data visualization.

This short communication explores the app’s architecture, its interactive interface, and its potential to reshape data visualization practices.

Methods

The most recent version of Color Quest is accessible at http://boydorr.gla.ac.uk/lucanelli/colorquest/.

Color Quest is developed using the R programming language [12] and integrates the ’shiny’ [13], ’colourpicker’ [14], ’colorBlindness’ [15], and ’ggplot2’ [16] packages. Once launched, the app presents a user-friendly interface with a single window, featuring multiple tabs (Fig 1). Users can select up to four colors using the provided color pickers located on the left sidebar. Upon scrolling down, users will reveal hexadecimal codes corresponding to their chosen colors. The app facilitates exploration across diverse visualization options housed under tabs like "Scatter Plot," "Line Plot," "Box Plot," "Histogram," and "Heatmap," each not only showcasing chosen colors but also offering simulations for various types of color blindness, including deuteranopia, protanopia, and desaturation. Although many color figures align well with individuals who have color blindness, there exists a limitation in terms of compatibility with black-and-white printers [5]. In light of this consideration, Color Quest takes a practical step by including a black and white (desaturation) option, to ensure visuals remain comprehensible even in grayscale print, enhancing inclusivity and accessibility across various modes of presentation.

Fig 1. Interface of the Color Quest app, freely available at http://boydorr.gla.ac.uk/lucanelli/colorquest/.

Fig 1

Open in a new tab

Notably, the "Heatmap" tab empowers users to explore data’s visual representation via a continuous color scale, enriching the spectrum of visualization possibilities.

An additional distinctive aspect of Color Quest lies in its ability to allow users to upload their own images (in jpg or png format), enabling users to evaluate how their plots, charts, diagrams, or other visual content, would appear to individuals with color vision impairments. Images are not saved on the server, ensuring users’ security and privacy.

To ascertain the initial impact and usability of this tool, a user feedback mechanism was implemented within the app interface. This system captures live, anonymous user input concerning the tool’s effectiveness and user-friendliness through a combination of quantitative ratings and qualitative comments.

In addition to desktop usage, Color Quest is optimized for seamless visualization on tablets and smartphones, enabling users to directly capture images of existing plots using their phones. This feature ensures accessibility and convenience across various devices.

Both the code and its documentation can be found in the supplementary material and are continuously updated on my GitHub repository: https://github.com/lucanelli/colorquest. On GitHub, users will find detailed documentation, step-by-step instructions, explanations of code functions, and use-case examples.

Discussion

Color Quest aligns with ongoing discussions about accessibility in data visualization [7]. It serves as both a practical tool for data visualization enthusiasts and a platform for raising awareness about the significance of inclusive design. The app’s versatility is showcased through simulations that illustrate how various visualization types, including scatter plots and histograms, would appear to individuals with color vision deficiencies and in black and white [5], fully answering the call for inclusivity in scientific communication [4].

The app’s utility extends beyond academia to practical contexts like presentations, posters, conferences, and lectures, offering a broader impact in various communication settings. In particular, the users’ ability to upload their pre-existing plots and figures, gives Color Quest a versatility that spans a range of scientific domains. For instance, in medicine, Color Quest can be helpful in future genetic research studies, ensuring that subtle genetic variations visualized are discernible by researchers across the spectrum of color vision. In epidemiology, should a future outbreak arise where data visualization plays a critical role in decision-making, Color Quest could be instrumental in crafting universally comprehensible color-coded infection rate maps, facilitating more informed and rapid response strategies. Similarly, in ecology and biodiversity conservation Color Quest may play a transformative role by ensuring that maps detailing biodiversity hotspots or environmental degradation areas are accessible to policymakers and the general public, irrespective of their color vision capabilities.

The software’s open-source nature, rooted in principles of transparency, community collaboration, and ongoing improvement, allows researchers, developers, and the community to both benefit from its features and contribute to its evolution, ensuring long-term sustainability, adaptability, and fostering a collaborative innovation ecosystem.

Conclusions

Color Quest’s development and deployment mark a significant step in data visualization. By harmonizing aesthetics with accessibility, the app empowers users to select colors that align with their narrative while ensuring inclusivity. The impact of this tool extends beyond boundaries, enabling equitable communication of insights to diverse audiences. In an increasingly data-centric world, the evolution of tools like Color Quest contributes to visually engaging and universally comprehensible information dissemination.

Supporting information

S1 File. Striking image.

(PNG)

pone.0290923.s001.png (1.5MB, png)
S1 Text

(TXT)

pone.0290923.s002.txt (16.6KB, txt)

Acknowledgments

The ’Striking image’ used to represent this article online and on the journal homepage was generated using advanced artificial intelligence (AI) technologies, specifically ChatGPT and DALL-E, developed by OpenAI (https://www.openai.com).

Data Availability

The full code is available in the supplementary material, and the most updated version is freely available at the author’s github repository at https://github.com/lucanelli/colorquest.

Funding Statement

The author received no specific funding for this work.

References

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Decision Letter 0

Mohamed Rafik N Qureshi

18 Sep 2023

PONE-D-23-26146Color Quest: An Interactive Tool for Exploring Color Palettes and Enhancing Accessibility in Data VisualizationPLOS ONE

Dear Dr. Nelli,

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A significant improvement is necessary to the paper "Color Quest: An Interactive Tool for Exploring Color Palettes and Enhancing Accessibility in Data Visualization" since it fails to meet a number of quality criteria.

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Reviewers' comments:

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Reviewer #1: No

Reviewer #2: Yes

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Reviewer #1: No

Reviewer #2: N/A

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Reviewer #1: No

Reviewer #2: Yes

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Reviewer #1: Yes

Reviewer #2: Yes

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Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Authors of this document asserted an Interactive Tool for Exploring Color Palettes and claiming that this can enhance Accessibility in Data Visualization.

This paper has a good structure with a good description about the proposed solution which looks promising but it doesn’t provide any examples of using it. References are from reputable publishers and also up-to-date.

No literature review was included, which was intended to offer a thorough grasp of the research problem and the various existing or similar solutions. This paper also lacks both metrics for assessing the proposed solution and a verified analysis of its efficacy.

Reviewer #2: The manuscript introduces "Color Quest", an interactive tool developed to address accessibility issues in data visualization, specifically considering individuals with color vision deficiencies. This is a significant contribution, given the growing emphasis on inclusivity and accessibility in scientific communication.Overall, the manuscript is well-structured and written clearly. The abstract succinctly summarizes the paper's main points and provides a clear understanding of the tool's purpose and potential impact.

Specific Comments:

Line 5: "Glsagow, UK" seems to be a typo. It should be corrected to "Glasgow, UK".

Lines 12-13: You mentioned the ability of the tool to visualize color palettes on custom images. Including a brief mention of the feature allowing users to upload their images might provide a more rounded view of the app’s capabilities in the abstract.

Line 66: The connection between the limitation with black-and-white printers and the black and white option in the tool could be clarified further.

Lines 78-79: Mentioning that the code is open-source and available at GitHub is a great point. It would be good to also state if any documentation or community guidelines are available for potential contributors.

Lines 80-95: The discussion highlights the potential impacts of the tool very well. Adding a glimpse of future developments or enhancements could add more depth to this section. E.g., mentioning a few specific examples or case studies where the tool could be beneficial might give a more grounded view of its potential applications.

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Decision Letter 1

Mohamed Rafik N Qureshi

16 Nov 2023

Color Quest: An Interactive Tool for Exploring Color Palettes and Enhancing Accessibility in Data Visualization

PONE-D-23-26146R1

Dear Dr. Nelli,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

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Mohamed Rafik N. Qureshi, Ph.D.

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Thank you for your updated version of "Color Quest: An Interactive Tool for Exploring Color Palettes and Enhancing Accessibility in Data Visualization"

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

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Reviewer #2: All comments have been addressed

Reviewer #3: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #2: Yes

Reviewer #3: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: N/A

Reviewer #3: N/A

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #2: Yes

Reviewer #3: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #2: Yes

Reviewer #3: Yes

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6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #2: The revision is sufficient. Further information on the related literature has been provided, future developments have been addided to the Discussion and grammatical issues have been corrected.

Reviewer #3: I thank the author for their effort and time in revising this paper. Please consider fixing this minor typo in the manuscript:

"that approximately that approximately" → "that approximately"

**********

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Reviewer #2: No

Reviewer #3: Yes: Ghazal Kalhor

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Acceptance letter

Mohamed Rafik N Qureshi

9 Jan 2024

PONE-D-23-26146R1

PLOS ONE

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Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 File. Striking image.

    (PNG)

    pone.0290923.s001.png (1.5MB, png)
    S1 Text

    (TXT)

    pone.0290923.s002.txt (16.6KB, txt)
    Attachment

    Submitted filename: RESPONSE to reviewers.docx

    pone.0290923.s003.docx (22.2KB, docx)

    Data Availability Statement

    The full code is available in the supplementary material, and the most updated version is freely available at the author’s github repository at https://github.com/lucanelli/colorquest.

    Articles from PLOS ONE are provided here courtesy of PLOS

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