Why the return-on-investment of open data is the wrong question

Based on brief remarks I gave at Open Data Day DC 2015.

Open data is a set of practices. It is a community around those practices. And it is a set of values that we bring to problems that we’re tasked to solve.

Open data is a lot like voting. On election day, voting is a messy process, and not everyone wants to do it. It’s expensive to buy and maintain all of those voting machines, to take the day off from work, to do recounts when something goes wrong. It’s confusing. There are a lot of local positions I’m not familiar with and I need the help of experts to effectively participate.

But if someone walked up to you at 10pm election night and asked you to demonstrate the return on investment of all of the day’s efforts, I think you’d say that that’s not the right question. You have to look back, first, at the history of how we got to vote. And then you have to be patient and look forward for change and evolution in government and the new policies that might be enacted years if not decades later, to know whether the vote was “successful.”

So it goes for open data. We should invest in learning and perfecting the methods of open data — how you publish it, get it, analyze it, and so on — and about the values of open data. But always keep in mind that these skills and ideas are in the service of the problems that brought us to use open data in the first place: government corruption, consumer choice in the marketplace, more effectively telling a story, widening access to justice, and so on. Those are big problems, and when we bring open data to the table we must remember to evaluate it in the context of playing the long game for specific social change or other goals.