Graphs & Visualizations

Data visualizations, charts, and graphs play a crucial role in conveying complex information in a digestible and engaging format. There are a number of key considerations and techniques to keep in mind when creating visualizations that are inclusive and informative for all users.

Design and Color Choices

Ensure sufficient contrast between the colors used for text and data points versus those of background elements.

• Color Contrast: Ensure sufficient contrast between the colors used in your visualizations, including text, data points, and background elements. Adhere to WCAG color contrast guidelines (at least 4.5:1 for normal text and 3:1 for large text) to make the content easily readable for individuals with low vision or color blindness.
• Colorblind-Friendly Palettes: Avoid relying solely on color to convey information. Use patterns, textures, or labels in addition to color to differentiate data series and ensure accessibility for individuals with color vision deficiencies.
• Minimalism and Clarity: Strive for a clean and uncluttered design. Avoid excessive visual elements that can create confusion or overwhelm users, especially those with cognitive disabilities or who use assistive technologies.

Labels and Descriptions

• Clear and Descriptive Titles: Provide a clear and descriptive title for your visualization that summarizes the key message or insight.
• Axis Labels and Legends: Include clear and concise labels for axes, legends, and other key elements within the visualization. Use plain language and avoid jargon or abbreviations.
• Text Alternatives: Provide text alternatives (e.g., alt text for images, captions for videos) that accurately describe the visual content, including data trends, key takeaways, and any other relevant information.
• Data Tables: Consider including a data table alongside your visualization to provide a tabular representation of the data, allowing users to access the information in a non-visual format. Also see the table formatting guide.

Supplemental Formats

• Long Descriptions: For complex or highly detailed visualizations, provide a separate long description that explains the visual content in greater detail. This can be accessed through a link or provided as an alternative format.
• Sonification: Explore the use of sonification, which translates data into sound, to provide an alternative sensory experience for individuals with visual impairments.
• Interactive Features: If your visualization includes interactive features (e.g., tooltips, hover effects), ensure they are accessible via keyboard navigation and screen readers. Provide clear instructions and feedback for interactive elements.

Building Your Data Visualization

• Accessible Tools and Technologies: Choose data visualization tools and technologies that support accessibility features, such as generating accessible output formats (e.g., SVG with appropriate ARIA attributes).
• Testing and User Feedback: Test your visualizations with assistive technologies and gather feedback from users with disabilities to identify and address any accessibility barriers.
• Ongoing Improvement: Continuously seek ways to improve the accessibility of your data visualizations by staying updated on best practices and incorporating user feedback.

Creating accessible data visualizations is crucial for ensuring that everyone, regardless of their abilities, can access and understand the information presented. By following the principles and techniques outlined in this article, you can craft visualizations that are both visually appealing and inclusive, enabling all users to benefit from the insights your data has to offer.

Remember, Accessibility is an ongoing commitment. By prioritizing inclusivity in your data visualization practices, you contribute to a more equitable and accessible digital world for all.