Today, I’m excited to publish a new in-depth report on how data practitioners can approach their work through a lens of diversity, equity, and inclusion: “Do No Harm Guide: Applying Equity Awareness in Data Visualization.” Co-authored with Alice Feng and supported by the Tableau Foundation, this work builds on our previous report from August 2020, which we presented at the VIS2020 conference last October. The goal of the guide is not to provide a roadmap for what to do or not do, but to encourage thoughtfulness in how analysts work with and present their data.
In making this guide and its associated toolkits, we conducted more than a dozen interviews with nearly 20 people who work with data to hear how they approach inclusivity in their work. The final report has more than 20 different sections that we hope will be helpful for anyone working with data take a more inclusive and equitable approach to their work.
To give you a quick preview of what you can get in the Do No Harm Guide, here is a summary of the section on how to think about how to treat the “other” category in your data. This is an issue that affects many data communicators and is complicated by issues of sample size, survey design, and language. As communicators, we need to recognize that the term “other” literally others people and communities, and emphasizes how they differ from the norm.
Yet there are alternatives to the word “other” that we think data communicators can take in their work. We identify six possible alternatives to the word “other”:
- Another race
- Another group
- All other self descriptions
- People identifying as other or multiple races
- Identity not listed
- Identity not listed in the survey
In the guide, we note that “some of these terms are more verbose and may not fit as nicely in a table or under a bar in a bar chart, but they are more inclusive.”
Over the coming weeks and months you will see more about this report and the associated toolkits here and on my social media feeds. Alice and I will be doing numerous podcast interviews, roundtable discussions, and more. We hope this initial report lays the groundwork for even more research and conversation about these important issues.
There are a number of ways you can read and interact with the report and the supporting materials: First, check out the full report at the Urban Institute. Second, visit the Tableau Foundation’s Do No Harm webpage dedicated to the report with supporting videos and other materials. And be sure to visit Tableau’s Racial Equity Data Hub, which contains a number of resources to help the data visualization community grow and evolve as racial equity advocates.
