Equity-Focused Dataviz Workshop



Workshop: How do we visualize inequality without promoting it? How can we communicate social outcomes in ways that inspire positive change?

When data represents groups of people, it’s inescapably interpreted through the audience’s prior knowledge, assumptions, biases and stereotypes about the groups being visualized. This makes visualizing social data unique from other topics. It also means that common visualization techniques that are safe in other domains can be harmful when visualizing data about people from minoritized communities.

A recent peer-reviewed study from 3iap, in collaboration with researchers at UMass Amherst’s HCI-VIS Lab, show that certain common types of data visualizations, meant to raise awareness of social disparities, may actually reinforce disparities by encouraging harmful stereotypes about the people being visualized.

To raise awareness about our findings and help the data visualization community produce more equitable social-data visualizations, 3iap offers workshops tailored to designers, analysts, journalists, and any other interested data communicators.




The workshops help chart makers:

  1. Identify and articulate the hidden biases pervasive in charts and graphs covering social outcome disparities.
  2. Develop intuition for surprising ways that social psychology can influence audiences’ perceptions of information.
  3. Learn alternative design approaches to effectively present equity-focused dataviz, in ways that create awareness and inspire change, while upholding the dignity of the people being visualized.

The workshops are for any groups interested in designing more equitable data visualizations, but we’re especially interested in speaking with:

  • Advocacy groups using data for social good
  • Data journalists covering any aspects of inequality or systemic racism
  • DEI-focused HR or people analytics analysts
  • Social program evaluation experts
  • Public-health communicators reporting outcome disparities
  • Government agencies or non-government organizations sharing statistics about people based on their race, ethnicity, gender or other memberships in marginalized communities

If this sounds like your organization, then please get in touch. You can reach us in one of the following ways:





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