Data divides and umbrellafication
Jesse Lichtenstein in “Transparency for All”, writing for Wired:
The concern that open data may simply empower the empowered is not an argument against open data; it’s an argument against looking at open data as an end in itself. Massive data dumps and even friendly online government portals are insufficient. Ordinary people need to know what information is available, and they need the training to be conversant in it. And if people are to have more than theoretical access to the information, it needs to be easy and cheap to use. That means investing in the kinds of organizations doing outreach, advocacy, and education in the communities least familiar with the benefits of data transparency. If we want truly open government, we still have to do the hard work of addressing basic and stubborn inequalities. However freely it flows, the data alone isn’t enough.
Yes and yes. Most government data is policy-level, which means to understand and act on that data, you not only need to be data literate, but also civically literate to transform knowledge into power. Call me a constructionist, but community organizing creates a stronger sense of agency than statistics.
And “cheap” data inconsiderately presented can be harmful. The worst data abuses come from trying to use policy-level, non-contextualized or incomplete data to inform individual decision-making. For example, I had to add this caveat to the Boston Bike Crash Map after getting several anxiety-producing inquiries:
This data alone is not appropriate for making routing decisions. The presence or absence of incidents in a location should not be used to determine the relative safety of biking there as this data does not include ridership or traffic information; i.e. a location may contain less incidents because bikers know to avoid it.
For decision making, I’ve come to call this phenomenon the “umbrellafication” of data—after the service that boils the weather forecast down to a simple yes/no answer to “Do you need an umbrella today?” Unfortunately, like trying to portray crime as a spectrum of green to red, issues and datasets that can be easily synthesized and presented are the exception, not the rule.