The Library of Missing Data Sets by Mimi Onuoha
Brilliant. As Mimi Onuoha explains:
What is a Missing Data Set?
“Missing data sets” are my term for the blank spots that exist in spaces that are otherwise data-saturated. My interest in them stems from the observation that within many spaces where large amounts of data are collected, there are often empty spaces where no data live. Unsurprisingly, this lack of data typically correlates with issues affecting those who are most vulnerable in that context.
The word “missing” is inherently normative, it implies both a lack and an ought: something does not exist, but it should. That which should be somewhere is not in its expected place; an established system is disrupted by distinct absence. Just because some type of data doesn’t exist doesn’t mean it’s missing, and the idea of missing data sets is inextricably tied to a more expansive climate of inevitable and routine data collection.
Here are a few missing datasets:
When the US Foreign Intelligence Court meets
All extinct languages
Number of nuclear weapons Israel has
Number of EU migrants currently in the United States
People excluded from housing due to criminal records
Undocumented immigrants for whom prosecutorial discretion has been used to justify release or general punishment
For more, see here.
Onuoha describes herself as an artist and researcher. Her previous pieces include writing for National Geographic voices, and she has taught a class on the art of digital mapping at NYU.
As she points out, because a dataset is missing, it doesn’t have to stay that way. We now have data on the number of civilians killed in interactions with the police, thanks to the Guardian The Counted project. What’s brilliant about Unuoha’s contribution, is that it’s not about missing data, but about missing datasets. Missing data is where you have a dataset but it’s incomplete. A missing dataset however is a hole in our thinking; a missing concept. So as much as anything her project is about a form of “epistemic closure” or belief systems that are unable to recognise their gaps.
In this day and age of “post-truth,” “fake news” and a certain kind of lack of purchase of the empirical, her project is very timely.
(h/t @baratunde here.)