About Us

Welcome to Uncommoned Goose, a newsletter that brings you stories, insights, and resources about data for the public good. Inspired by the folk poem The Goose and the Common, we explore the tension between shared resources and private interests in an age of information. Just as the poem warns against enclosing the commons, we explore the possibilities of data-driven accountability as well as the consequences of disappearing data access.

Each edition of Uncommoned Goose dives into topics at the intersection of data science, information policy, and current events. We introduce you to interesting datasets and find engaging narratives hiding within them to provide new perspectives. Data is never neutral but encodes fascinating social values that are opportunities to tell new stories, to challenge power structures, and to create a fairer information society.

Whether you're a policy wonk, a tech worker, or someone who simply cares about how information shapes our world, Uncommoned Goose offers stories and resources to help you make sense of it all and to connect with others. Join us as we use data to reclaim our information commons and serve the public interest.

The Goose and the Common

"The Goose and the Common" is a folk protest song that originated in the 17th or 18th century in England in response to wealthy landowners' expanding private property claims on land that had traditionally had been shared in common:

The law locks up the man or woman
Who steals the goose from off the common
But leaves the greater villain loose
Who steals the common from off the goose.

The law demands that we atone
When we take things we do not own
But leaves the lords and ladies fine
Who take things that are yours and mine.

The poor and wretched don’t escape
If they conspire the law to break;
This must be so but they endure
Those who conspire to make the law.

The law locks up the man or woman
Who steals the goose from off the common
And geese will still a common lack
Till they go and steal it back

About me

Brian C. Keegan is a social, data, network, and information scientist. He is an assistant professor in the Department of Information Science at the University of Colorado Boulder.