More Completely Applying Open Source Methods to Data

Nat Torkington shares a realization on O’Reilly Radar, that the goal of opening public data can learn more from open source than just how we access the end product. He does a good job of considering both tools and certain social models. From version control to leadership and even changing attitudes to towards the life “after release” of data, there is a lot to think about here. I especially like the implication that working in a manner across the board borrowing much more thoroughly from open source presents a possible solution to data accuracy issues, a common criticism of implementing transparency.

I would have really liked to see much more consideration on the values inherent in open source. Mostly he sticks to how this informs opportunities for sharing credit and managing interactions between contributors and users. Maybe I am thinking beyond his simple proposition, considering the hacker ethic more than the common denominator open source methodology. I think adding that ethos could help address some of the other criticisms of transparency, namely the idea that technology can produce beauty and, more importantly, effect change may help fix focus on outcomes as much as process.

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