Lessons learned from the Open Data front lines
right now about his experiences with two open data projects, Open New Zealand and data.govt.nz.
Most of experiences are consistent with what we have learned at Backstage.
- You can build it but they won't come
All successful open source projects build communities of supportive engaged developers who identify with the project and keep it productive and useful. - it costs money to make existing data open. That sounds like an excuse, and it's often used as one, but underneath is a very real problem: existing procedures and datasets aren't created, managed, or distributed in an open fashion. This means that the data's probably incomplete, the document's not great, the systems it lives on are built for internal use only, and there's no formal process around managing and distributing updates.
- identify the high-value datasets, where great public policy comment, intra-government optimisation, citizen information, or commercial value can be unlocked. Even if you don't buy into the cost argument, there's definitely an order problem: which datasets should we open first? It should be the ones that will give society the greatest benefit soonest. But without a community of users to poll, a well-known place for would-be data consumers to come to and demand access to the data they need, the policy-making parts of governments are largely blind to what data they have and what people want.
- If this is open data, where's my damn transparency?...the UK's MySociety defined what success is to them: they're all about building useful apps for citizens, and open data is a means not an end to them.
Although most of Nat is talking about is to do with Government data, there are certainly a lot of parallels which can apply to Backstage and the ´óÏó´«Ã½'s public data.
- We're put up data in the past and few people have used it. The thought was that it was too complex but actually that wasn't the case, it was the lack of knowledge that it even existed. People still ask if they can get programme information from backstage, although we've been talking about /programmes for years.
- The cost issue is also key, backstage isn't too bad, we are very aware that this is public money and only sponsor things which related directly to what were doing or trying to get to. Our biggest cost is our virtual machine servers (welcomebackstage.com) which are used to provide data sets and prototypes from across the ´óÏó´«Ã½.
- We do sit on a lot of high value datasets but unlike governments a lot of them are either shared or not ours to give away. We do however try and convince the owner of the data to make available in a open data format for people to remix.
- If you look back to when Backstage was setup, it was a response to the Graf report to why the ´óÏó´«Ã½ wasn't open and transparent enough. So for us open data is also a means and not the end of the road
Its reassuring to know we're sharing the same experiences as others in the industry and hope to share more of what we've learned over these 5 years in the future. Nat's last paragraph sums up nicely
So, after nearly a year in the Open Data trenches, I have some advice for those starting or involved in open data projects. First, figure out what you want the world to look like and why. It might be a lack of corruption, it might be a better society for citizens, it might be economic gain. Whatever your goal, you'll be better able to decide what to work on and learn from your experiences if you know what you're trying to accomplish.
Second, build your project around users. In my time working with the politicians and civil servants, I've realised that success breeds success: the best way to convince them to open data is to show an open data project that's useful to real people. Not a catalogue or similar tool aimed at insiders, but something that's making citizens, voters, constituents happy. Then they'll get it.
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