Data Visualizations

Data visualizations, like charts and graphs, are best for highlighting trends, patterns, and outliers in data, while tables are more effective for presenting precise numerical values and detailed information

Best Practices for Data Visualization Accessibility

• Use descriptive titles and labels
  • Clearly label axes, legends, and data points.
  • Use meaningful titles that summarize the key message of the visualization.
• Provide text alternatives
  • Include alt text or long descriptions for charts and graphs.
  • Summarize key insights in surrounding text or captions.
• Ensure color accessibility
  • Avoid relying solely on color to convey information.
  • Use high-contrast color palettes and colorblind-friendly schemes.
  • Use patterns or textures in addition to color for differentiation.
• Use accessible chart types
  • Prefer simpler chart types (e.g., bar charts, line graphs) over complex ones (e.g., 3D pie charts).
  • Avoid clutter and unnecessary embellishments.
• Ensure keyboard and screen reader compatibility
  • Ensure interactive visualizations are navigable by keyboard.
  • Use ARIA (Accessible Rich Internet Applications) roles and labels for screen reader support.
• Ensure responsive and scalable design
  • Make sure visualizations are responsive to different screen sizes.
  • Allow zooming without loss of clarity or context.
• Provide data tables
  • Offer the underlying data in a tabular format for screen readers and users who prefer raw data.
• Test with real users
  • Conduct usability testing with people who have various disabilities.
  • Use accessibility evaluation tools (e.g., WAVE from webaim.org).

Creating Accessible Data Visualizations

Since every program has different ways to do things, we’ve found some links with program-specific instructions to make tables more accessible.