Applying Best Practices to Open Data

by Joe Brockmeier - Mar. 17, 2010Comments (0)

Open Knowledge Foundation

Hot on the heels of open source, open data has been coming into fashion — but finding it is not always easy and few projects have given much thought to managing the data after its release. O'Reilly's Nat Torkington has, though, and has put up a thoughtful post about the importance of not only releasing open data, but applying the best practices of open source to open data.

A truly successful open source project requires more than tossing code over the wall where others can download it. It requires a community to maintain the code, promote the project, and help sustain the project. Likewise, Torkington writes, there's "no reason why open data shouldn't bring the same opportunities to data projects." This is an excellent idea and it'd be good to see lessons learned by open source projects applied to open datasets.

Some of that is already going on. In a follow-up, Torkington links to a few posts from the Open Knowledge Foundation, which has come up with a Open Knowledge Definition (OKD) taken from the Open Source Initiative's Open Source Definition. This includes everything from content like movies and books to government info, and sets 11 criteria that a work has to meet to be considered "open."

The tools we have today make creating, accessing, and modifying data easier than ever before in human history. It's a shame that so much data is being produced and released with little thought given to seeing that it's updated or used effectively. As Torkington writes:

Finally, we need to change attitudes and social systems. Data is produced as the product of work done, and is rarely conceived of as having a life outside the original work that produced it. Some datasets will (some won't--think of how many projects fail to interest anyone but the person who started them). This means thinking of yourself not just as the person who does the work, but the person who leads a project of interested outsiders and (in some cases) collaborators and who is building something that will last beyond their time. This is not a natural mindset within government nor, in many cases, science. Funding and budgeting systems at the moment may prevent this, and would need to change.

What he doesn't touch on is that, just as with open source, there may be business opportunities around open data that would help fund the curation of open data and possibly the creation of new open data and content. I'm not at all convinced that only "closed" content and data can support a business model. There's value in sifting through all the open content and data and offering it in a form that is more easily digestible by users, for example.

The Creative Commons folks have gone a long way towards coming up with reasonable license models for open content (though not all CC licenses would meet the OKD), but not much in the way of managing content or organizing community around it. It's good to see open data getting more widespread attention. Open source development is, if not a solved problem, an area that's close to maturity. Open data is the next frontier that needs taming.