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Data Storytelling in a Diverse World

We all share a responsibility to ensure the language, symbols, and point of view we use in our data stories reflect one, fundamental principle: to Do No Harm.
The Do No Harm Guide from the Urban Institute is grounded in the belief that we can work together to build a more equitable and inclusive world by using data with sensitivity and care.

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VIDEO SUMMARY

Picture This: Doing Good Data Means Doing No Harm

This video provides a quick overview of the 10 recommendations from the Guide to help you understand how to present data through a more diverse, equitable, and inclusive lens.

Meet the authors: Tableau’s Renee MacLeod interviews Jonathan Schwabish and Alice Feng

Authors Image Collage

Season 2 | Episode 6

If Data Could Talk

Do No Harm: Data, Viz, Equity and Inclusion

Jon Schwabish, Alice Feng, and Channing Nesbitt join Andy to discuss their combined efforts in developing, publishing, and promoting the Do No Harm Guide: a toolkit that focuses on how data practitioners can approach their work through a lens of diversity, equity, and inclusion.

View Guide Resources

This is a sampling of books, organizations, and other resources that may help you and your organization build an equitable approach to data and data visualization.

Selected Bibliography

  • Catherine D'Ignazio and Lauren F. Klein, Data Feminism (Cambridge, MA: MIT Press, 2020).
  • Sasha Costanza-Chock, “Design Justice: Towards an Intersectional Feminist Framework for Design Theory and Practice,” in Proceedings of the Design Research Society, ed. Cristiano Storni, Keelin Leahy, Muireann McMahon, Peter Lloyd, and Erik Bohemia (London: Design Research Society, 2018), 529–40.
  • Sarah Williams, Data Action: Using Data for Public Good (Cambridge, MA: MIT Press, 2020).
  • G. Cristina Mora, Making Hispanics: How Activists, Bureaucrats, and Media Constructed a New American (Chicago: University of Chicago Press, 2014).
  • Safiya Umoja Noble, Algorithms of Oppression: How Search Engines Reinforce Racism (New York: NYU Press, 2018).
  • Ruha Benjamin, “Race after Technology: Abolitionist Tools for the New Jim Code” Social Forces 98, no. 4 (2019): 1–3.
  • Virginia Eubanks, Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor (New York: St. Martin's Press, 2018).
  • Witney Battle-Baptiste and Britt Rusert, eds., WEB Du Bois's Data Portraits: Visualizing Black America (Hudson, NY: Princeton Architectural Press, 2018).
  • Tactical Technology Collective, Visualizing Information for Advocacy (Berlin: Tactical Technology Collective, 2013).

Organizations

Other Resources