Jonathan Schwabish and Alice Feng of Urban Institute have written a guide and associated toolkits to support data practitioners in diversity, equity, and inclusion.

General recommendations include:

• People-first language
• Consideration of missing groups
• Use alternatives to "other" category
• Reflect lived experiences
• Color, icon, and shape considerations

Schwabish writes: "Through rigorous, data-based analysis, researchers and analysts can add to our understanding of societal shortcomings and point toward evidence-based actions to address them. But when data are collected and communicated carelessly, data analysis and data visualizations have an outsize capacity to mislead, misrepresent, and harm communities that already experience inequity and discrimination."

If you work with data or the communication of it, this resource may be of help to you!

Visit the Guide