Open Source Model for the Science Fields

August 3, 2009 CollabNet VersionOne

We know that using an open source model for software development drives innovation, reveals bugs and fixes more quickly, and allows for creative minds to collaborate in ways that just can't happen with proprietary code. Because of this, we have been seeing more open source software projects emerge over the past few years. That's not to say that there aren't issues. Businesses are still working out the kinks in how they can sponsor and encourage open source software while trying to figure out how to pay the bills and profit. After all, few can volunteer all of their time. In addition, credit needs to go where credit is due.

In the science fields, sharing research and data has been the norm, but the process differs from the open source software model. Typically a scientist starts his/her research, makes discoveries, writes up the findings, and then publishes in leading journals. Then, and not until the creator's name is firmly attached, do others get the data. Eventually, the code or data gets shared. Now, however, various branches of science are looking more closely at the open source software model.

The main concern of scientists has been getting credit where credit is due. The introduction of licenses, similar to those we use for open source software, will protect the discovery process, while encouraging collaboration, and verification. The added benefit is that there is no need to wait for publication.

Personally, I find this exciting. It means more minds can get in on the research from the very beginning, and is not academically exclusive. The more variety of people and the larger the set of eyes looking at a project or problem, the great the likeliness that it will speed up the discovery and testing process.

Transparency is a huge bonus in software development, and I think we'll find the same is true in the world of science.

There is much concern in the science arena that someone will swoop up the public research and take credit for it, that people "undeserving" will water down the reputations of those more deserving. I think just the opposite will happen. And it's sad that the importance of reputation manages to rise above the possibility of improving processes and increasing the likeliness of discovering error or new information.

Apparently many science researchers are resistant to sharing data, even after the publication in a journal. Science should not be allowed to be a closed system. All the processes, the procedures, the data capture methods, and the data itself should be exposed at the earliest possible moment.

I'm excited to see sites and resources like the following:

There is currently a lot of resistance from scientists to open source their projects, but as awareness increases about the benefits of transparency emerge, I think we'll see more and more scientific research on the web along with special licenses to protect the originators through the discovery process.

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