Data visualizations are an increasingly popular way to present complex data sets. They transform raw data into visual formats like charts, graphs, maps, and diagrams, allowing some people to grasp patterns, trends, and relationships at a glance. However, if data visualizations are designed without accessibility in mind, they can present barriers due to their emphasis on visual presentation. Improving features through accessibility features like alt text, sufficient contrast, and simplified design can make your data presentation more accessible.

The accessibility of data presentations is largely dependent on the expertise of developers and designers to understand capabilities of their chosen platform. Developers should also familiarize themselves with core accessibility concepts such as inserting images, configuring color palettes, labeling interactive controls, and other basic tasks that can also enhance accessibility.

Note: Different data tools and platforms provide different supports for creating accessible data visualizations and no authoring tool is inherently better at creating accessible content. Even if you have made use of your platform's accessibility options, you should provide your data in alternate formats to ensure access to the broadest audience.

Tips for improving the accessibility of data visualizations

Select a visualization type that best represents your data. Ensure that it's easy to interpret for users who may be unfamiliar with your dataset. Be aware of accessibility barriers caused by highly dynamic widgets, animations, and other interactions.

Different tools provide different levels of support for accessible data visualization. The accessibility of visual data is largely dependent on the expertise of developers and designers to understand the capabilities of their chosen platform. Accessibility features such as ALT text for images, well-labeled interactive controls, accessible color palettes, and keyboard operability can provide a more inclusive and accessible experience for some users.

Note: even after using the tools in your chosen platform, it is likely that you will need to provide alternate content to ensure equitable access for the broadest audience.

Overview of Accessibility in PowerBI

Visit the Tableau Accessibility FAQ 

Make sure your users have the information they need to effectively read and interact with the visualization. Provide a text overview of the data. Include a descriptive title, a summary of the information, including trends or conclusions, links to table data and other information to orient the user. If your data visualization is interactive, include instructions on using any filters, queries, or other interactive elements.

Include descriptive alt text for images, charts, and other non-text elements. This allows screen readers to narrate the content to visually impaired users. Be detailed but concise in your descriptions. For complex visualizations, your alt text might consist of a summary and a link to a lengthier description. 

Insufficient contrast, such as yellow text on a white background, can make it difficult for your users to read and understand your data. Use a tool like the Color Contrast Analyser to ensure that your background and foreground colors combine for a clear and legible presentation.

Make sure the data visualization is keyboard operable. Users should be able to navigate through the data visualization and easily recognize and activate any controls, form fields, filters, or other interactive elements. Arrange your elements in a logical tab or keyboard order to reflect the meaning of your visualization. Before you publish your visualization, unplug your mouse and use your tab, enter, and spacebar keys to navigate your application and activate any forms, filters, or other controls.

Even when you carefully plan for accessibility, it’s likely you will need to provide your data in additional formats to ensure access to all. Provide a text overview of the visualization, including a descriptive title, a summary of the information, links to source data, explanations of trends or other findings, and other information to orient the user. Include data tables alongside your visualizations to provide a structured, tabular representation of the data.

As with other digital information, be certain your alt formats are accessible. In particular, ensure tables have appropriate headers and summaries and that supporting content is presented in well-formed and structured text.

The following websites offer a wealth of information about accessibility and data visualization. 

University of Washington: Data Viz Accessibility in 2021

University of Wisconsin: Accessible Data Visualizations

Harvard University: Data Visualizations, Charts, and Graphs

MIT: Making data visualizations more accessible

Smashing Magazine: An Accessibility-First Approach to Chart Visual Design

Digital.gov: Data Visualizations

Sarah L. Fossheim: An Intro to Designing Accessible Data Visualizations