This is not new material but of interest to those monitoring the development of the open paradigm in all sectors of human life.
At the Mozilla Foundation blog, Mitchell asks himself two important questions. One: how does open science differ from open source models and what extra difficulties does it face; Two: given those extra difficulties, what are the prospects for its development.
We monitor this topic in a special area of our wiki; here.
Excerpt 1: How open science differs from open source?
“1. A lot of scientific effort is expensive. Itâ€™s hard to work in many areas without being tied to an institution that provides the equipment, the labs and other necessary support. This greatly reduces an individualâ€™s ability to break out of the standard way of doing things.
2. A lot of scientific efforts require long periods of outlays before getting meaningful results â€“ itâ€™s harder to find incremental projects that can demonstrate value (whether economic or social) quickly.
3. Itâ€™s much more difficult to â€œscratch oneâ€™s own itch. â€œ Someone choosing to work in many scientific fields is unlikely to be solving his or her own immediate problem. The result may be years away, unknown, and not directly applicable to his or her own life. This is quite different from software development, where many people get involved to fix something that is bugging their daily experiences.
4. Thereâ€™s no accepted set of free and unencumbered tools and building block for the life sciences. This problem was raised by Richard Jefferson of cambia.org, who notes that the technologies used to pursue the scientific process are encumbered by patents in such a way that the end result is hard (or impossible) to use and share freely. Itâ€™s as if a patent on a compiler (or all compilers) applied to any code that had been compiled. Richard’s pithy summation of this problem is: â€œthereâ€™s no LAMP stack.â€ (Thanks to Richard for permission to attribute this to him, which is required under the Chatham House Rule under which SciFoo operated.)
5. Thereâ€™s already a recognition system in place through the peer-reviewed journals. This mechanism has a variety of problems itself and may be due for change. But even so, there is an accepted review, recognition and advancement system for the sciences outside of collaboration.
6. Collaboration often needs to occur between institutions rather than individuals. This makes it harder to get started than simply having a few people decide to try something.”
Excerpt 2: What then, are the Prospects for Open Science?
“Given the issues with “open science” how might progress towards openness be made?
1. It’s unlikely that those with a big financial stake in the current arrangements will change. This obviously includes the commercial ventures aiming for large returns on their investment. It probably also includes the major research and development institutions who may not be public companies but who are deeply involved in the current system. If you’re an academic institution and you’ve spent millions of dollars outfitting labs and have a set of people working and studying at your institution assuming the research and its results will be treated a certain way, it’s hard to make big changes. So even if one takes the position that these organizations should change (which I’m not necessarily advocating) I think it’s unlikely that leadership toward Open Science will come from here.
2. It’s more realistic to expect change around the edges than at the very center of the system. Periodically I read about diseases that could probably be treated, but exist mostly in impoverished areas. So there’s very little economic reward for the necessary research, development and deployment. I could imagine organizations concerned with alleviating these diseases to be more inclined to find ways to collaborate, particularly if relevant patents have expired.
3. There is usually a hierarchy of research organizations and universities; the “top tier” schools are more able to get research funds and to capitalize on the results of their work. But, there are massive numbers of very smart and very motivated people at other organizations. It may be that collaborative scientific techniques will develop at unanticipated places that aren’t well positioned in the current system.
4. It may be that successful Open Science doesn’t start at the central, biggest problems. It may grow by solving pieces of problems. Free compilers existed before the complete GNU Linux operating system; the same incremental change may occur with Open Science. Sadly, many of the big problems are the health topics where people’s lives are at stake.
5. The realm known as “Citizen Science” may well lead the way. Citizen Science is based on large numbers of people working together. Since those participants aren’t expected to have scientific training, there are a whole set of problems that can’t even be approached through this method. But we may be surprised at the areas where Citizen Science can move our understanding forward.”