What are the best ways to design data visualizations for accessibility?

1 Color contrast and palette

When creating data visualizations, color is one of the most important aspects to consider. It can help you highlight key data points, create categories, and convey emotions. However, it can also create barriers for people with color vision deficiencies, low vision, or who use screen readers. To ensure your visuals are accessible, you should use high contrast colors for text and background (such as black on white or white on dark blue) and test your color combinations with tools like WebAIM's Color Contrast Checker. Additionally, avoid using color alone to convey meaning; instead add labels, symbols, patterns, or textures to differentiate data elements (for example, use dashed or dotted lines for different series in a line chart or icons for different groups in a pie chart). Finally, choose a color palette that is accessible and harmonious by using tools like ColorBrewer or Adobe Color.

2 Font size and style

Font is an important part of data visualization, as it can affect readability, clarity, and aesthetics. However, font can also pose difficulties for people with dyslexia, low vision, or who use assistive technologies. To avoid this, ensure that the font size is large enough - at least 12 points for body text and 18 points for headings - and use a clear and simple font style such as Arial, Helvetica, or Verdana. Additionally, use a consistent font style and avoid using too many different styles that could create visual clutter or confusion.

3 Labels and legends

Labels and legends are an essential element of data visualization, as they can help explain and annotate data. To ensure accessibility for people with cognitive impairments, low literacy, or who use screen magnifiers, it's important to use descriptive and concise labels and legends that are accessible, logical, visible, and aligned. For example, "Average monthly income in US dollars" or "Red: High risk, Yellow: Medium risk, Green: Low risk". Avoid using vague, ambiguous, inaccessible, illogical, hidden or scattered labels and legends that can cause misunderstanding or misinterpretation or create barriers or biases.

4 Formats and alternatives

Data visualization involves formats and alternatives, which can help you select the best way to present your data, such as charts, tables, maps, or images. However, formats and alternatives can also affect the accessibility and usability of your data depending on the device or platform. To avoid this, you should use the most appropriate and effective format for your data that is also accessible and compatible. Additionally, provide alternative and complementary formats for your data, such as text descriptions, captions, summaries, or audio. This will help ensure that your data is easy to understand, access, view, perceive and interpret.

5 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?