Should Data Collected For Academic Research Get Intellectual Property Protection?
from the the-big-questions dept
Michael Scott points us to a blog post by a political science professor, Jeff Yates, who in a previous life had been a lawyer. In the blog post, he discusses the social norm within academic circles of freely sharing data used in research, and wonders if there shouldn’t be some sort of intellectual property protection on the data. He isn’t claiming that there definitely should be — he’s just exploring the topic, and questioning whether or not it makes sense.
Of course, as many proponents of open research and open education systems will tell you, it’s difficult to see why such data should get any sort of protection or how that actually helps towards the goal of the pursuit of knowledge. Countless studies have shown that having more folks examine and analyze the data is a much better way of speeding up the process of getting to more interesting findings. Slowing down that process seems quite counterproductive to everyone involved. If some of the issue is that it’s “unfair” for others to do research on data they did not collect, that can and should be mitigated by giving credit where credit is due. In academic circles, citations and giving credit is a lot more standard (and respected). It doesn’t always work, but it certainly can mitigate any “downside” to sharing data. If someone else makes a giant breakthrough with the data you collected, there’s no reason the original data collector can’t use that fact to his or her advantage — especially in getting future grants or publicity.
The other claim, of course, would be that without such protectionism, there is less incentive to collect that data. On that subject, we actually have quite a bit of empirical data that suggests this claim is simply incorrect. The US does not have database rights, while Europe does (such rights are loosely similar to what is being asked for here — providing some sort of protectionism for “sweat of the brow” collection of data, rather than any creativity put on top of it), and yet when you compare similar database industries in the US to Europe you quickly discover that they’re much bigger in the US than in Europe.
The reasoning makes sense, once you think it through. Because the data are not locked down and can be used in many more ways, the data become a lot more valuable, and open up many more opportunities for lots of companies to benefit. That leads to more experimentation and more innovation… and greater demand for the data itself. From that there are plenty of incentives to make sure the collection of the data is continually enhanced, because it benefits so many people downstream (in economic terms, it’s an example of the Coase Theorem at work).
Now, while the economic setup in the academic world may seem to be slightly different (researchers aren’t necessarily trying to maximize revenue), the overall incentive structure remains effectively the same (and money is still a part of it all). Freeing up your data so that more people can analyze it increases the overall value of the data and is more likely to lead to additional breakthroughs or interesting findings from that data. In turn, that can lead back to more interest for the original data collector and more opportunities to do more or to be involved in more relevant projects. Locking up the data, on the other hand, takes away many of those incentives for no clear benefit.