Accessibility in Data Visualization: Making Charts Everyone Can Understand

11 minute read • Accessibility & Design

Data visualization is powerful—but only if everyone can access it. Yet millions of users face barriers when interacting with charts and graphs: colorblind individuals struggling to distinguish between lines, screen reader users hearing "image" instead of insights, keyboard-only users unable to interact with tooltips, and people with cognitive disabilities overwhelmed by complex visualizations.

These aren't edge cases. 8% of men and 0.5% of women have some form of color vision deficiency. Globally, over 1 billion people live with disabilities. When you publish an inaccessible chart, you're potentially excluding 10-20% of your audience—and in many cases, violating legal accessibility requirements (WCAG 2.1 Level AA is legally mandated for government and many business websites).

The good news? Accessible data visualization isn't complicated or expensive. With the right techniques—colorblind-safe palettes, proper alternative text, keyboard navigation, and thoughtful design—you can create charts that work for everyone while often improving the experience for all users.

In this guide, you'll learn:

Understanding the Accessibility Barriers in Data Visualization

Before fixing accessibility issues, let's understand who's affected and how.

Barrier 1: Color Vision Deficiency (Colorblindness)

Who it affects: 8% of men, 0.5% of women (primarily red-green colorblindness)

Common problems:

Example failure: A line chart showing "Revenue (green) vs. Expenses (red)" appears as two brown/yellow lines to someone with deuteranopia (most common type). The entire chart becomes useless.

Barrier 2: Screen Reader Incompatibility

Who it affects: Blind users, low-vision users relying on screen readers

Common problems:

Example failure: A blind user navigating a dashboard hears "Image. Image. Image." with no context about sales trends, regional breakdowns, or key metrics.

Barrier 3: Motor Disabilities and Keyboard-Only Users

Who it affects: Users with motor disabilities, power users, assistive technology users

Common problems:

Example failure: A user with Parkinson's disease cannot steadily hover over a data point to read its tooltip. A keyboard-only user cannot tab to chart elements to explore data.

Barrier 4: Cognitive Disabilities and Cognitive Load

Who it affects: Users with cognitive disabilities, ADHD, dyslexia, elderly users

Common problems:

Example failure: A dashboard with 12 charts, blinking numbers, and auto-updating every 2 seconds overwhelms users with ADHD or cognitive processing difficulties.

WCAG 2.1 Level AA Requirements for Data Visualization

The Web Content Accessibility Guidelines (WCAG) 2.1 Level AA is the international standard for web accessibility. Here's what it means for charts:

Success Criterion 1.1.1: Non-text Content (Level A)

Requirement: All non-text content (charts, graphs, infographics) must have a text alternative.

What makes good alt text:

Bad alt text examples:

Good alt text examples:

Success Criterion 1.4.1: Use of Color (Level A)

Requirement: Color cannot be the only way information is conveyed.

Implementation strategies:

1. Add patterns or textures to distinguish data series beyond color alone.

2. Use direct labels instead of relying on legend colors

3. Add data point markers with different shapes

Success Criterion 1.4.3: Contrast (Minimum) - Level AA

Requirement: 4.5:1 contrast ratio for text, 3:1 for large text and UI components

For charts, this means:

Tools to check contrast:

Colorblind-Safe Palettes: Specific Recommendations

The easiest win for accessible data visualization is choosing the right colors. Here are proven, colorblind-safe palettes.

Example of an accessible column chart

Palette 1: IBM Color Blind Safe (Recommended)

Designed by IBM's accessibility team, tested with all types of color vision deficiency.

const ibmPalette = {
  blue: '#648FFF',    // Primary
  violet: '#785EF0',  // Secondary
  magenta: '#DC267F', // Accent 1
  orange: '#FE6100',  // Accent 2
  yellow: '#FFB000'   // Highlight
};

Why it works: Maximum perceptual distance between colors, works for all colorblind types.

Use cases: Line charts (up to 5 lines), bar charts, categorical data

Palette 2: Paul Tol's Vibrant (7 colors)

Created by cartographer Paul Tol specifically for scientific visualization.

const tolVibrant = [
  '#EE7733', // Orange
  '#0077BB', // Blue
  '#33BBEE', // Cyan
  '#EE3377', // Magenta
  '#CC3311', // Red
  '#009988', // Teal
  '#BBBBBB'  // Grey
];

Why it works: Tested with deuteranopia and protanopia simulations, high contrast.

Use cases: Multi-series line charts, stacked bars, complex visualizations

Palette 3: Avoid These Common Failures

❌ Red-Green combinations:

// DON'T USE TOGETHER
const bad = {
  positive: '#00ff00', // Green
  negative: '#ff0000'  // Red
};

✅ Safe alternatives:

// Use blue-orange or purple-orange instead
const good = {
  positive: '#1f77b4', // Blue
  negative: '#ff7f0e'  // Orange
};

Testing Your Palette

Online simulators:

Process:

  1. Create your visualization with your chosen palette
  2. Take a screenshot
  3. Upload to Coblis and test all 8 types of color vision deficiency
  4. Verify you can still distinguish all data series
Example of a radar chart with accessible design

WCAG 2.1 Level AA Compliance Checklist for Dashboards

Use this checklist before publishing any dashboard or data visualization:

Visual Design:

Screen Reader Support:

Keyboard Navigation:

Interactive Features:

Mobile/Touch:

Tools for Testing Accessibility

Automated Testing:

Manual Testing:

Color and Contrast:

Process:

  1. Run automated tools (axe, Lighthouse)
  2. Fix all flagged issues
  3. Test with keyboard only
  4. Test with screen reader (NVDA or VoiceOver)
  5. Test with colorblind simulator
  6. Test on mobile device
  7. Get feedback from users with disabilities (user testing)

Conclusion

Accessible data visualization isn't just a legal requirement—it's good design. When you design for users with disabilities, you often improve the experience for everyone:

Your action plan:

  1. Audit current visualizations using axe DevTools and Lighthouse
  2. Switch to colorblind-safe palettes (IBM or Paul Tol recommended)
  3. Add alt text and ARIA labels to all charts using the formulas above
  4. Implement keyboard navigation for interactive charts
  5. Test with real users with disabilities if possible

Making data accessible to everyone isn't just the right thing to do—it expands your audience, improves SEO, ensures legal compliance, and makes your visualizations clearer for all users. Start with one improvement today, and build accessibility into your workflow going forward.

For specialized charting solutions with built-in accessibility features, check out platforms like 5of10.com that prioritize inclusive design.

Resources: