I'm kicking myself because I've been taking far too narrow an interpretation of "an open source approach". I've been focused on getting people to release data. That's the data analogue of tossing code over the wall, and we know it takes more than a tarball on an FTP server to get the benefits of open source. The same is true of data.
Open source discourages laziness (because everyone can see the corners you've cut), it can get bugs fixed or at least identified much faster (many eyes), it promotes collaboration, and it's a great training ground for skills development. I see no reason why open data shouldn't bring the same opportunities to data projects.
And a lot of data projects need these things.
I've been saying for a while that open data is a sort of new frontier. Open source is relatively wide spread and there is a general low hum of understanding about it in many places. For me, I sum it up by saying to people that they need to understand that their "code is worthless".
The next step is coming to understand about open data, and why we should care. Why we should convince people that their "data is worthless".
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