Making Data Visualization More Accessible to Blind and Visually Impaired People

Web-based data visualizations are largely inaccessible to blind and visually impaired people who use screen readers, assistive technology that reads on-screen items as text-to-speech. This excludes millions of people from the possibility of probing and interpreting information often presented in the form of graphs, such as election results, health statistics and economic indicators.

When a designer tries to make a visualization accessible, best practice is to include a few sentences of text describing the chart and a link to the underlying data table, which falls short of the rich reading experience offered to sighted users. .

An interdisciplinary team of researchers from MIT and beyond is working to create user-friendly data visualizations for screen readers that provide an equally rich experience. They prototyped several visualization frameworks that provide textual descriptions at varying levels of detail, allowing a screen reader user to drill down from high-level data to more detailed information with just a few keystrokes.

The MIT team embarked on an iterative co-design process with collaborator Daniel Hajas, a researcher at University College London who works with the Global Disability Innovation Hub and lost his sight at the age of 16. . They collaborated to develop prototypes and conducted a detailed user study with blind and visually impaired people to gather their feedback.

“Researchers can see connections between problems and be aware of potential solutions, but very often they miss them a bit. Ideas from people who have lived experience with a certain specific, measurable problem are really important for many disability-related solutions. I think we found a really good fit,” says Hajas.

They created a framework to help designers think systematically about how to develop accessible visualizations. In the future, they plan to use their prototypes and design framework to create a user-friendly tool that could convert visualizations into accessible formats.

MIT collaborators include co-lead authors and Computer Science and Artificial Intelligence Laboratory (CSAIL) graduate students Jonathan Zong, Crystal Lee, and Alan Lundgard, as well as JiWoong Jang, an undergraduate student at the University Carnegie Mellon who worked on this project during the MIT summer research. Program (MSRP) and lead author Arvind Satyanarayan, assistant professor of computer science who leads the visualization group at CSAIL. The research paper, which will be presented at the Eurographics Visualization Conference, won the honorable mention award for best paper.

“Pushing What’s Possible”

The researchers identified three design dimensions as critical to making visualizations accessible: structure, navigation, and description. Structure consists of organizing information in a hierarchy. Navigation refers to how the user moves through different levels of detail. Description is how the information is spoken, including the amount of information conveyed.

Using these design dimensions, they developed several visualization prototypes that emphasized ease of navigation for screen reader users. A prototype, known as a multiview, allowed individuals to use the up and down arrows to navigate between different levels of information (such as chart title as top level, legend as second level, etc.), and the right and left arrow keys to scroll through information at the same level (such as adjacent point clouds). Another prototype, known as Target, included the same arrow key navigation, but also included a drop-down menu of key chart locations so the user could quickly jump to an area of ​​interest.

“Our goal is not just to meet existing standards to make them usable. We really set out to do well-founded speculation and imagine where we can push what is possible with these existing standards. We didn’t want to limit ourselves to retrofitting tools designed for images,” Zong explains.

They tested these prototypes and an accessible data table, the existing best practice for accessible visualizations, with 13 blind and visually impaired screen reader users. They asked users to rate each tool on several criteria, including ease of learning and ease of locating data or answering questions.

“One thing that I found really interesting was how people were constantly testing their own assumptions or trying to create specific patterns as they moved through the visualization. The implication for the navigation is that you want to be able to orient yourself in the visualization so you know where the boundaries are,” says Lee “Can you accurately and easily know where the walls are in the room you’re exploring?”

Improved information

Users said both prototypes helped them identify patterns in data faster. Scrolling from high to deeper levels of information helped them get to information more easily than when navigating through the data table, they said. They also appreciated faster navigation using the target prototype menu.

But the data table got top marks for its ease of use.

“I expected people to be disappointed with the everyday tools compared to the new prototypes, but they still got a little hung up on the data board, probably due to their familiarity with it. This shows that principles such as familiarity, learning and friendliness are still important. No matter how ‘good’ our new invention is, if it’s not easy enough to learn, people might stick with an older version,” says Hajas.

Building on this knowledge, researchers are refining the prototypes and using them to create a software package that can be used with existing design tools to give visualizations an accessible and navigable structure.

They also want to explore multimodal solutions. Some study participants used different devices together, such as screen readers and Braille displays, or data sonification tools that transmit information using non-speech audio. How these tools can complement each other when applied to a visualization is still an open question, Zong says.

In the long term, they hope their work will lead to a careful rethinking of web accessibility standards.

“There is no one-size-fits-all solution for accessibility. Although existing standards do not assume this, they only offer simple approaches, such as data tables and alt text. One of the main benefits of our research contribution is that we provide a framework – different preferences and data representations are located at different points in this design space,” says Lundgard.

“We have worked hard to reduce the inequities that screen reader users face when extracting information from online data visualizations over the past few years, so we really appreciate this work and the insights that it adds to the existing literature,” says Ather Sharif, a graduate student who studies accessibility and visualization in the labs of Professors Jacob Wobbrock and Katharina Reinecke at the Paul G. Allen School of Computer Science and Engineering. from the University of Washington in Seattle, and who was not involved in this work.

“I like to think of it as a movement where we finally all come together and improve the experiences of a demographic that has been largely ignored, especially when presenting data through visualizations. Congratulations to Jonathan, Arvind and their team for this insightful and timely work! I’m looking forward to what’s next,” adds Sharif, who is the lead author of several recent articles related to accessible data visualizations.

Amy Bower, a senior scientist in the Department of Physical Oceanography at Woods Hole Oceanographic Institution, who suffers from a degenerative retinal disease and uses a screen reader extensively in her work as a researcher and also for basic life tasks, found the researchers’ explanations of the importance of co-design to be powerful and compelling.

“As a blind scientist, I am constantly looking for effective tools that will allow me to access the information conveyed in data visualizations. The layered approach taken by these researchers, which provides the ability to get the “big picture” from the data as well as explore the data points themselves, allows the user to choose how they wants to explore the data,” says Bower, who was also not involved in this work. “I believe that the ability to freely explore data is necessary not only to learn the ‘story’ the data tells, but to enable a blind researcher like me to formulate the next questions that need to be addressed to advance research. understanding in any field of study.”

This work was supported, in part, by the National Science Foundation.

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