Pretty much everybody in government should read this fantastic New York Times article Sharing of Data Leads to Progress on Alzheimer’s. On one hand the article is a window into what has gone wrong with science – about how all to frequently a process that used to be competitive but open, and problem focused has become a competitive but closed and intellectual property driven (one need only look at scientific journals to see how slow and challenging the process has become).

But strip away the talk about the challenges and opportunities for science. At its core, this is an article is about something more basic and universal. This is an article about open data.

Viewed through this lens it is a powerful case study for all of us. It is a story of how one scientific community’s (re)discovery of open principles can yield powerful lessons and analogies for the private sector and, more importantly the public sector.

Consider first, the similarities in problems. From the article:

Dr. Potter had recently left the National Institutes of Health and he had been thinking about how to speed the glacial progress of Alzheimer’s drug research.

“We wanted to get out of what I called 19th-century drug development — give a drug and hope it does something,” Dr. Potter recalled in an interview on Thursday. “What was needed was to find some way of seeing what was happening in the brain as Alzheimer’s progressed and asking if experimental drugs could alter that progression.”

Our government’s are struggling too. They are caught with a 20th-century organizational, decision-making and accountability structures. More to the point, they move at a glacial speed. On the one hand we should be worried about a government that moves too quickly, but a government that is too slow to be responsive to crises or to address structural problems is one that will lose the confidence of the public. Moreover, like in healthcare, many of the simpler problems have been addressed. citizens are looking for solutions to more complex problems. As with the scientists and Alzheimer’s we may need new models to speed the process up for understanding and testing solutions for these issues.

To overcome this 19th century approach – and achieve the success they currently enjoy – the scientists decided to do some radical.

The key to the Alzheimer’s project was an agreement as ambitious as its goal: not just to raise money, not just to do research on a vast scale, but also to share all the data, making every single finding public immediately, available to anyone with a computer anywhere in the world.

No one would own the data. No one could submit patent applications, though private companies would ultimately profit from any drugs or imaging tests developed as a result of the effort.

Consider this. Here a group of private sector companies recognize the intellectual property slows down innovation. The solution – dilute the intellectual property, focus on sharing data and knowledge, and understand that those who contribute most will be best positioned to capitalize on the gains at the end.

Sadly this is the same problem faced within governments. Sometimes it has to do with actual intellectual property (something I’ve recently argued our governments should abandon). However, the real challenge isn’t about about formal rules, it is more subtle. In complex siloed organizations where knowledge is power the incentives to maximize influence are to not share knowledge and data. Better to use the information you have strategically, in a limited fashion, to maximize influence. The result, data is kept as a scarce, but strategic asset. This is a theme I tackled both in my chapter in Open Government and in blog posts like this one.

In short, the real challenge is structural and cultural. Scientists had previously existed in a system where reputation (and career advancement) was built by hoarding data and publishing papers. While the individual incentives were okay, collectively this behavior was a disaster. The problem was not getting solved.

Today, it would appear that publishing is still important, but there are reputational effects from being the person or group to share data. Open data is itself a currency. This is hardly surprising. If you are sharing data it means you are doing lots of work, which means you are likely knowledgeable. As a result, those with a great deal of experience are respected but there remains the opportunity for those with radical ideas and new perspectives to test hypothesis and gain credibility by using the open data.

Unsurprisingly, this shift wasn’t easy:

At first, the collaboration struck many scientists as worrisome — they would be giving up ownership of data, and anyone could use it, publish papers, maybe even misinterpret it and publish information that was wrong.

Wow, does that sound familiar. This is invariably the first question government officials ask when you begin talking about open data. The answer, both in the scientific community and for government, is that you either believe in the peer-review process and public debate, or you don’t. Yes, people might misrepresent the data, or publish something that is wrong, but the bigger and more vibrant the community, the more likely people will find and point out the errors quickly. This is what innovation looks like… people try out ideas, sometimes they are right, sometimes they are wrong. But the more data you make available to people the more ideas can be tested and so the faster the cycle of innovation can proceed.

Whether it is behind the firewall or open to the public, open data is the core to accelerating the spread of ideas and the speed of innovation. These scientists are rediscovering that fact as our some governments. We’ve much to learn and do, but the case is becoming stronger and stronger that this is the right thing to do.