Visualization is just one form of data representation. Data visualizations such as charts, graphs, maps, and infographics, provide visual representations of information that help to make complex information easier for some people to understand. They are designed largely as an accommodation for sighted people for whom patterns, trends, and insights might be difficult to grasp from raw data alone.
While visualization is a widely used form of data representation, data can, and should be, represented using other forms as well for people who process information differently (e.g., using data tables, descriptions, or raw data sets that can be rendered using sound or haptics).
Key accessibility considerations
Accessibility needs vary by visualization type and complexity, but four broad design principles can improve accessibility in most cases. Use them—along with the listed resources and tools—to help ensure your data is accessible to all users, including those with disabilities.
Principle 1: Focus your data representation on essential insights:
- Identify the key takeaway(s)
- Remove unnecessary data
- Avoid excessive complexity or density
- For multi-dimensional data, split into separate views or allow users to add dimensions
Principle 2: Use clear descriptions to guide all users:
- Start with key information and context
- Include all necessary interpretive details
- Ensure hover-revealed information is accessible via keyboard and screen readers
- Use both visual and audible cues for dynamic changes to content
- Avoid static images of charts; if used, keep them simple and add alt text
Principle 3: Provide multiple means of representing the data:
- Present the data in a table alongside the visual representation.
- For datasets with more than 20 rows, include a representative sample of data in the table, instead of the entire dataset.
- Make raw data available for download
- Explore additional representation options available with your tool or platform (e.g., sonification).
Principle 4: Apply accessibility standards:
Ensure all data representations and interactive elements comply with the W3C’s Web Content Accessibility Guidelines (WCAG), such as:
- Ensure good color contrast between text and graphics and their backgrounds.
- Don’t use color as the sole means of differentiating between lines, bars, or other meaningful visuals; add different patterns or sizes.
- Check that interactive elements, such as links and buttons, can be reached navigating with a keyboard and are big enough to easily click.
- Be sure text is large enough to be easily readable and can be resized.
- Ensure the visualization scales well on a variety of screen and window sizes, without requiring horizontal scrolling.
Resources
Checklists
- Chartability is a comprehensive audit checklist designed to uncover specific data representation accessibility issues.
- UW Digital Accessibility Checklist is a core feature of the current website, providing an overview of common digital accessibility issues, accompanied by techniques related to specific technologies, tools, and platforms.
- UW Web checklist is a downloadable working spreadsheet that covers web accessibility checkpoints (mapped to WCAG), UW branding, and style.
UW resources
- Data Visualization: Accessibility Research Guide is a collection of data visualization tools, services, and resources maintained by UW Libraries.
- UW Deque University is a library of online asynchronous courses on digital accessibility available to anyone in the UW community.
- Consultation on digital accessibility is available through UW-IT Accessible Technology Services.
Business intelligence platforms
Tableau and Power BI help users create charts and dashboards without coding. While popular for visualizing data, these tools can pose challenges for users relying on screen readers or keyboard navigation, especially for highly complex and interactive visualizations. Ensuring accessibility requires thoughtful design and settings adjustments.
Get started:
- Tableau: Tableau Accessibility FAQ
- Power BI: Overview of Accessibility in Power BI
JavaScript (JS) charting libraries
JS charting libraries streamline the coding of custom data visualizations for the web, but their built-in accessibility varies. Web developers must assess and enhance output to ensure it meets accessibility standards.
The HighCharts JS charting library is one option that provides several tools out of the box to assist with implementing accessibility. It also comes with an education license.