Infoviz & Justice

The good folks at PolicyViz have some comments on challenges and approaches in bringing a racial equity sensibility to information visualization and presentation.

Although more people are thinking and writing about these issues, there hasn’t been much agreement around best practices for taking an equity lens to data visualization, especially as it applies to setting standards for entire organizations. As best we can, we have been reading a variety of posts and papers (a short list can be found below) and discussing ways we can develop a more diverse, equitable, and inclusive approach to presenting and visualizing data. We view this effort as just the beginning of our process and anticipate growing and expanding our work as we learn more and receive feedback from colleagues, partners, and readers.

To that end, we have identified eight areas in which researchers, analysts, and anyone working with data can be more inclusive in how they present their data.

• Using language with a racial equity awareness
• Ordering data labels in a purposeful way
• Considering the missing groups
• Using colors with a racial equity awareness
• Using icons and shapes with a racial equity awareness
• Demonstrating empathy
• Questioning default visualization approaches

I found the examples of ordering of data labels particularly striking; I can all too easily imagine making thoughtless choices with ugly unintended implications.

There is also a presentation with links to related resources.