Radical Cartography and Criminal Justice


Maps are among the oldest data visualizations, and as such they encourage centuries of dated and biased presuppositions on their “proper” nature and functionality. Critical cartography, which “challenges academic cartography by linking geographic knowledge with power” (Crampton & Krygier, 2005, p. 11), is a framework that enables its subscribers to discover and analyze meanings deeper than the superficial geospatial elements of a map. This expanded understanding of maps’ place in society “has been paralleled by a greater concern with the context in which mapping takes place, and the ways the cultural text of the map is performed” (Perkins, 2004, p. 385). In other words, maps are incompletely referenced as purely objective renderings of physical space, rather they are informed and shaped by, as well as facilitators in the formation of, culturally specific understandings of place. Failure to recognize this context in the analysis of maps discredits or distorts any and all conclusions subsequently made.

As digital technology democratizes the ability to generate, collect, and render geospatial data, maps have become an increasingly common part of modern life (MacEachren & Kraak, 2001, p. 1). Cartographers, data scientists, and other stakeholders must, therefore, acknowledge “that maps make reality as much as they represent it” and that the construction of these realities rests in the hands of virtually anyone with an internet connection. Further, as maps “actively construct knowledge, they exercise power” that translates into an influential “means of promoting social change.” (Crampton & Krygier, 2005, p. 15) A map is now that which can form new knowledge while simultaneously subverting and overturning predating perceptions of truth. Using critical cartography as an entry point, maps are a compelling, and consequently efficacious, method of visualizing controversial or contested social science and humanities data.



I have chosen to continue a theme from a previous lab by creating a visualization concerning policing in New York City.

The last few years saw an increase in the publicized demand for police accountability. In accordance with this demand, police departments began compiling and sharing datasets concerning their practices in the field. The growing number of records, which sometimes stretch back over a decade, offer an unprecedented view into a largely opaque institution. In “Look Before You Analyze: Visualizing Data in Criminal Justice,” Michael Waltz, a statistician with a focus on criminology, advises caution when using police data to make sweeping conclusions about policing (Maltz, 2010). Not only are self-reported datasets commonly incomplete, there are no standards for collecting and presenting data, so comparisons across departments are usually groundless. Even looking within a single department or precinct over multiple years, data can be inconsistent. What’s more, and what is particularly relevant to critical cartography, self-reported data is presumably that which the reporting party is comfortable with sharing. One of Maltz’s “favorite quotes” (Maltz, 2010, p. 1) is from the British economist Josiah Stamp:

“The Government are very keen on amassing statistics. They collect them, add them, raise them to the nth power, take the cube root and prepare wonderful diagrams. But what you must never forget is that every one of these figures comes in the first place from the chowty dar [village watchman]. Who just puts down what he damn pleases.” (Stamp, 1929)

Following this excerpt, Maltz entreats data scientists with an interest in criminal justice to be critical of their data source. This advice is certainly relevant to the practice of counter-mapping where police datasets are involved.

The following graphics reflect features of Maltz’s ideal visualization and provide inspiration for future directions with my own.

(“Vacant and Abandoned Building Finder – Chicago,” n.d.)

Maltz mentions the importance of understanding criminal justice data in context of the larger community. The features in this interactive visualization allow the user a great amount of control over the data they view, including many supporting levels of information.


image of mapping police violence visualization

(“Police killed at least 309 black people in the U.S. in 2016.,” n.d.)

Aesthetics should not be overlooked in the visualization design. The dark background and stark contrast of the animated data points add drama and tension to this vis which support the intent of the creators. Viewers of this graphic are meant to be moved emotionally and to be angered by the injustice of police violence. The creator of this visualization is Samuel Sinyangwe, and he used Carto to create his maps.


(Chicago Sun Times, n.d.)

Although not pertaining to police activity, the creators of this visualization are using maps in the expanded utility made possible by critical cartography. This map is not only a display of the physical location of homicides; rather, it serves as a virtual hub for community members dedicated to the quelling of violence in Chicago.



A computer with internet connection is necessary to recreate this lab. Also needed is an account on Carto, access to the NYC Open data portal, and sufficient storage for large datasets.



Using the NYC Open Data interface, search for and download the following datasets: NYPD district shapefiles and Police Complaints.

Upload the two layers to Carto with police districts layered below police complaints.

Rename the layers appropriately.

Select the “Analysis” option for the police district layer and choose “Intersect second layer.”

Choose the “Count” operation, then style the analysis such that the “Fill” is done by a “5 buckets” scale on the “count_vals” field. Now the depth of color in each police district as a direct relationship to the total number of complaints made in that district: the darker districts have more complaints.

Add “Widgets” for the description of offense field and the description of premises field. Both widgets give the user the option of color-coding  Police Complaint data points. Only one field can be color-coded at a time.

Orient the map such that the entire city boundary lies within the window.

The map is then ready to be published.



This visualization is only the first step towards a more robust, interactive design. The source data, as Maltz has warned, is largely incomplete between 2012 and 2015, so the plots of individual complaints are not entirely accurate. As always, many crimes go unreported or could be missing from the data for any number of reasons.

The color scheme does not account for visual impairments and the initial view (without any filters) could be overwhelming if viewed on a small screen.

Widgets are the only mode of interaction currently allowed. Future iterations would include more options for filtering and additional layers of data.


Future Directions

In his article, Maltz mentions the value in time series data for identifying and tracking trends (Maltz, 2010, p. 10-11). Like the police violence visualization (the second example), I would like to animate my graphic by taking advantage of the data and time fields in the dataset. To do so, I would need to research the approved time and date formats for Carto and modify the data to reflect those conventions.

I would also like to expand the aesthetics of my work beyond the current capacity of Carto. Crampton and Krygier note that the future of critical cartography, and that of its parent discipline as a whole, will be decided by “a variety of practitioners outside of the academy” who thus have the freedom “to explore what [radical cartography] means in practice” (Crampton & Krygier, 2005, p. 17). This visualization offers the opportunity to join creatives in reimagining the meaning of a map. For example, the Atlas of Radical Cartography, along with many independent artists (like sl;g;kldfh british national portrait gallery) have used maps as a way to navigate concepts and intangible phenomena. Police violence could certainly be presented in this way.

Another direction involves crowdsourced data and community monitored maps. Using internet-based collaborative tools makes this quite simple (Perkins, 2004, p. 386), and again Crampton and Krygier describe how that practice is an additional subset of radical cartography:

Everyday mapping, whether performative, ludic, indigenous, affective and experiential or narrative, creatively illuminate the role of space in people’s lives by countering generalized and global perspectives.” (Crampton & Krygier, 2005, p. 25)

Creating a map as a collaborative exercise in resistance to police violence, one that is released from the conservative constraints of longitude and latitude and is instead enriched by personal understandings of space and place, would be a long term goal for maps of the kind generated in this lab.



Chicago Sun Times. (n.d.). Homicide Watch Chicago. Retrieved July 5, 2017, from http://homicides.suntimes.com/homicides/map/2017/

Crampton, J. W., & Krygier, J. (2005). An Introduction to Critical Cartography. ACME: An International Journal for Critical Geographies, 4(1), 11–33.

MacEachren, A. M., & Kraak, M.-J. (2001). Research Challenges in Geovisualization. Cartography and Geographic Information Science, 28(1), 3–12. https://doi.org/10.1559/152304001782173970

Maltz, M. D. (2010). Look Before You Analyze: Visualizing Data in Criminal Justice. In A. R. Piquero & D. Weisburd (Eds.), Handbook of Quantitative Criminology (pp. 25–52). Springer New York. https://doi.org/10.1007/978-0-387-77650-7_3

Perkins, C. (2004). Cartography – cultures of mapping: power in practice. Progress in Human Geography, 28(3), 381–391. https://doi.org/10.1191/0309132504ph504pr

Police killed at least 309 black people in the U.S. in 2016. (n.d.). Retrieved July 5, 2017, from https://mappingpoliceviolence.org/

Stamp, J. (1929). Some Economic Factors in Modern Life. P.S. King and Son, 258–259.

Vacant and Abandoned Building Finder – Chicago. (n.d.). Retrieved July 5, 2017, from http://chicagobuildings.org/




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