Data Visualization Module

Create a critical data visualization (or two) on prison agriculture in the United States. Access PDF of this module here. Consider how the visualization(s) will draw on and/or connect key concepts (e.g. racial capitalism, criminalization, labor, discipline, abolition, etc.). When creating the visualization, incorporate one or more of the principles of feminist data visualization from the book Data Feminism (D’Ignazio and Klein 2020). For instance, your visualization may:

  • Leverage emotion and affect to make prison agriculture visceral
  • Communicate your positionality and/or demonstrate reflexivity as it relates to prisons and prison agriculture
  • Challenge the limits of data classification systems, such as hierarchies and binaries, in prisons and in prison agriculture
  • Integrate multiple voices (e.g., subjugated voices) to create a more complete picture of the issues at hand
  • Highlight or draw attention to what’s likely missing or undercounted in the data
  • Contextualize the data – find a way to add back missing context of racial-gendered capitalism
  • Play with presentation’s rhetoric, showing the effects of different labeling choices or presentations of the data on how it may be interpreted 
  • Or otherwise critically draw attention to issues of power and injustice

We understand both “data” and “visualization” to be flexible constructs inclusive of traditional statistical graphing techniques (e.g., plots, word clouds, bubble charts), mapping and story maps, photographic art, graphic design, protest art, infographics, zines, hybrid visualizations, and more. You may use any data visualization tools including R, observable, Excel, story mapping platforms, word cloud generators, and more.

We encourage you to leverage data from the Prison Agriculture Lab (2022).

Accompanying your visualization(s), write a three-paragraph summary explaining your visualization, what it depicts, what data sources you consulted and used, and how your creation incorporates one or more principles of feminist data visualization. What drew you to create your visualization? What’s special about it? Why does it challenge power imbalances and injustices? Cite all your sources, including the data sources.


D’Ignazio, C. and L. Klein. 2020. Data Feminism. Cambridge: MIT Press

Prison Agriculture Lab Website 

Recommended Readings, Data Sets, and Example Visualizations

Chang, W. 2022. R Graphics Cookbook, 2nd ed. Sebastopol, CA: O’Reilly Media, Inc.

Dear Data. n.d. The Project.

Johnson, K. R. 2021. Two Regimes of Prison Data Collection. Harvard Data Science Review 3.3

Lupi, G. and S. Posavec. Dear Data. New York: Princeton Architectural Press.

Prison Policy Initiative Data Visualizations

This is not an atlas. e-book and maps.

United States. Bureau of Justice Statistics. Census of State and Federal Adult Correctional Facilities, 2019. Inter-university Consortium for Political and Social Research [distributor], 2022-06-16.

Visualizing Abolition

Wickham, H. and G. Grolemund. 2017. Data visualization. R for Data Science.