What would feminist data visualization look like?

Seeing the whole world is a fantasy that Michel DeCerteau calls the “totalizing eye” and Donna Haraway calls “the God Trick”. This is the first image taken of the whole earth in 1967. From Wikipedia.

The eyes have been used to signify a perverse capacity — honed to perfection in the history of science tied to militarism, capitalism, colonialism, and male supremacy — to distance the knowing subject from everybody and everything in the interests of unfettered power. The instruments of visualization in multinationalist, postmodernist culture have compounded these meanings of disembodiment.

The visualizing technologies are without apparent limit. The eye of any ordinary primate like us can be endlessly enhanced by sonography systems, magnetic resonance imaging, artificial intelligence-linked graphic manipulation systems, scanning electron microscopes, computed tomography scanners, color-enhancement techniques, satellite surveillance systems, home and office video display terminals, cameras for every purpose from filming the mucous membrane lining the gut cavity of a marine worm living in the vent gases on a fault between continental plates to mapping a planetary hemisphere elsewhere in the solar system.

Vision in this technological feast becomes unregulated gluttony; all seems not just mythically about the god trick of seeing everything from nowhere, but to have put the myth into ordinary practice. And like the god trick, this eye fucks the world to make techno-monsters.

— Donna Haraway in “Situated Knowledges: The Science Question in Feminism and the Privilege of Partial Perspective/Feminist Studies” (1988)

The God Trick! Is this not the rhetorical premise and the seductive promise of most data visualization? To see from the perspective of no person, no body? Our appetite for such perspectives is fierce, “gluttonous”, as Haraway characterizes it.

1. Invent new ways to represent uncertainty, outsides, missing data, and flawed methods

While visualizations — particularly popular, public ones — are great at presenting wholly contained worlds, they are not so good at visually representing their limitations. Where are the places that the visualization does not go and cannot go? Can we put those in? How do we represent the data that is missing? Andy Kirk has an incredible talk about the Design of Nothing that surveys the field in regards to how designers make decisions about representing uncertainty, including zeros, nulls and blanks. Can we push more designers to take these methods into consideration? Can we ask of our data that it point to its own outsides?

Map to Not Indicate, 1967, by the art collective Art & Language. The map depicts only Iowa and Kentucky and then proceeds to list the many things that NOT represented on it. Part of the Tate Collection.

2. Invent new ways to reference the material economy behind the data.

Akin to this question of data provenance, we also need to ask about the material economy behind the data. What are the conditions that make a data visualization possible? Who are the funders? Who collected the data? Whose labor happened behind the scenes and under what conditions?

From a Public Lab research note by Eymund Diegal about mapping sewage flows in the Gowanus Canal. Note the people on boats doing the mapping and the balloon tether that links the camera and image back to their bodies.

3. Make dissent possible

While there are plenty of “interactive” data visualizations what we currently mean by this is limited to selecting some filters, sliding some sliders, and viewing how the picture shifts and changes from one stable image to another stable image as a result. These can be powerful methods for diving into a contained world that consists of stable images and stable facts. But as we know from Wikipedia editing wars and GoogleMap Controversies the world is not actually bracketed so conveniently and “facts” are not always what they appear to be.

From Field Notes III: Geography of the Children of Detroit by the Detroit Geographical Expedition and Institute, 1971. Warren and her colleagues used this map and the overall report to argue for the need “Black planning” that empowered black citizens to make decisions for their communities.
Two screenshots from Brooke Singer’s ToxicSites.us which presents maps, visualizations and stories about every superfund site in the USA.

What else?

These are just three design suggestions that point towards a feminist ethics and politics of data visualization. What else? I’d love to hear what other aspects of data visualization we could re-think to make it more situated, more feminist and ultimately, more responsible. Post your thoughts here in the comments or @kanarinka on Twitter and let’s continue the conversation.


Certeau, M. & Rendall, S. (1984). The practice of everyday life. Berkeley: University of California Press.



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Catherine D'Ignazio

Catherine D'Ignazio

Assistant Prof of Urban Science and Planning, Dept of Urban Studies and Planning. Director, Data + Feminism Lab @ MIT.