All Times EDT
Keywords: Accessibility, Graphic Design, Color, Data Visualization
The term “accessibility” is often associated with assistive technology, but the data visualizations created by technology also need to be accessible. Graphs are powerful tools to communicate the message to the audience, but the audience has to be able to read the graph first, including people with disabilities. Therefore, we demonstrate two examples of improving accessibility in data visualizations generated by the R package ggplot2, and the concepts are technology agnostic because they apply to other software as well. The first example shows three trends of different colors in the same plot. However, people with color blindness cannot see color, so they would have difficulty identifying which trend belongs to which group. A solution is to change the line types and the point shapes, so that each trend can be distinguished even in the absence of color. The second example contains two aligned barplots that compare the precipitation of Seattle and Phoenix. Nevertheless, some tiny precipitation bars for Phoenix can hardly be seen, especially for people with low vision. As a result, they may be concerned about missing data. We can fix the issue by adding the exact numbers on top of the tiny bars, so people know that the data exist. In addition, the default unit for precipitation is inches, but some people outside the US are not familiar with this measurement scale. By adding a secondary y-axis in millimeters (mm), we reduce their mental efforts of unit conversion. These revisions to the graph improve not only accessibility, but also readability. Thus, accessibility benefits not only people with disabilities, but also improves the overall user experience. Accessibility in data visualizations increases the size of the audience pool, translating to a greater business impact.