Open Data, Open Standards, and Community Activism
BY David Eaves | Tuesday, May 29 2012
Over at the United State Environmental Protection Agency’s (EPA) blog there was a great piece posted a few days ago, "Using the Toxic Release Inventory to Build Power in Communities.
The piece, written by Clean Air Coalition Executive Director Erin Heaney, is a great mini case-study. For the Clean Air Coalition, the Toxic Release Inventory (TRI) — a database published by the EPA that tracks pollution from facilities across the United States that are required to report by law to report emissions — serves as an organizing point around creating broader campaigns and mobilizing community members.
In the case of the Clean Air Coalition, they build their event and training around the data set. As Heaney describes:
We have built power by developing grassroots leaders who run campaigns that advance environmental justice in Western New York. For example, in March we trained our membership on how to use the TRI. We spent the first half of the training learning about history of TRI and about how it was through communities standing up and saying that they needed more information about the environmental conditions in their communities that led to the creation of the TRI. Our members learned who reports to TRI, as well as when and how the data is verified. Afterward, we headed over to the computer lab to learn how to use the EPA TRI tool myrtk.epa.gov. Our members dug into the data for their neighborhoods and learned which companies were polluting, what they were emitting and what the health effects of those emissions were.
Such organizing would have been hard to do 10 years ago, and will get easier as the costs of computer access continues to decline, and, hopefully, more government data is made available. Heck, we need to corner Heaney and get her to share her syllabus and other materials she used to create and run this event so that more organizations like hers can replicate it. My own sense is that activists and non-profits have not even begun to tap the power of open data. Indeed, what I often find striking is that there aren't more people like Heaney out there, using public data to drive education, build capacity and community and, of course, drive campaigns. Non-profits and advocacy groups frequently use data, but generally for planning and research, and then more selectively in communications. It is still relatively rare to invite participants right into the process of playing with it, and analyzing it, directly. Over time, I suspect that methodologies to do just this are going to become more commonplace as not only more government data becomes public, but as cost of collecting data for the purpose of activism drops. For example, the "Air Quality Egg" Kickstarter project — which distributes air quality measuring devices — received orders for over 1,110 devices and raised $144,592, a full $105,000 more than it set out to collect. The potential for using the open data collected by this project is very interesting.
That said, there is also a deeper lesson in this. Specifically, it is about making data easier to use. Much of the conversation around this has, of course, focused on making data available. But what really enabled Heaney’s work is not merely the data’s availability. Nor was it about training. Buried beneath it all is a story of standardization. The fact that there are standard ways of representing geographic data (in this case, the location of pollution sources) means there are lots of easy and intuitive ways to show this data to people. For example, in Canada, a software development team I worked with was able to take a similar database and map it so that people could identify major polluters near them.
This is why data standards and schemas matter. They reduce the barrier to entry around data by making it easier to build tools and other ways to interface with information. They make analysis, training, engagement and all the other things citizens might want to do cheaper and scalable. In short, common schemas further democratize data — they make it accessible to a broader group of people. This story is a great example of why activists and non profits should not only care about data, but advocate for common data schemas for pollution data, real estate values, crime data, fisheries stocks or a number of other datasets locked away within government. Once standardized it is more likely there will be tools that will enable citizens to understand and access the information about policies that impact them — information that was previously available only to powerful interests that could not only afford the data, but also the special tools needed to analyze and make use of it.
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