Scientific knowledge, especially publicly funded knowledge, should be returned freely to society. Sadly, current solutions for allocating funding conflict with this ideal. To fund research, we enforce artificial scarcity using the concept of 'Intellectual Property'. Artificial scarcity allows us to adjust the value of knowledge to match the costs associated with its creation. Intellectual property concerns are similar in academia, industry, and the arts, but I restrict reflection to the area which most affects me : Science.
Academia runs on reputation, and requires accurate attribution of intellectual property. This discourages behaviors that benefit science at large. Collaboration is avoided out of fear that it could cause one to lose ownership of ideas. Data are not shared if there is a possibility that said data cold yield more publications. Useful intermediate results that are too small to publish are kept secret. Techniques may be kept 'trade secrets'. These behaviors are bad for science, but academics are pressured into them to survive. Similar can be said for all industries : protecting a product ensures that the market rewards those who make the original investment, but this problem is not one of free-markets. All economic models must solve the problem of funding the most capable individuals.
Can open science resolve this conflict? Not yet, but it suggests a few immediately useful steps. Resource allocation is simplified when resources are abundant.
- Open science lowers the cost of research by reducing artificial scarcity.
- Open access publishing frees researchers from large, expensive, library subscriptions.
- Open source scientific software frees researchers from expensive proprietary software.
- Open source operating systems and software reduces the cost of computing.
- Open source hardware and small scale fabrication technologies reduce material costs.
When grants no longer support library subscriptions and matlab licenses, the same amount of money can support more researchers, and more research. For theorists, this can mean reducing the cost of research to the cost of living, and university affiliation is no longer a feudal necessity. With these simple steps, we can confine competition for resources to covering the cost of living and physical material costs of experiments.
The remaining costs of competition can be lessened by following an open science etiquette. Share data freely. Let people know what you're working on, if not the details. Publish often so that useful results are not withheld. If you find someone working on a similar problem, collaborate and discuss how to redirect efforts to reduce overlap. Clearly state the nature of contributions to a manuscript. Give attribution liberally, and acknowledge sources of inspiration explicitly. Take advantage of self publishing and non-peer reviewed repositories like arxiv, which, while they do not provide a stamp of legitimacy to the research, preserve attribution. Encourage people to build upon your work, and accept that they have many of the same ideas, goals, and competencies, as you. When someone does an experiment you had planned, be excited that you get to see the results earlier, and talk to the authors to look for possible collaborations and ways to reduce future overlap. There are many interesting problems to solve before we can eliminate anti-collaborative pressures in science.
Open science may be a social good, but can it also be a selfish good? Publishing open access can lead to broader dissemination of your results, bolstering reputation. Releasing code under open licenses provides and opportunity to demonstrate competence, and demonstrates your value to the scientific community. Using open source languages for scientific computing make your code available to students, educators, and outsiders, who would otherwise be unable to use your code. Source code licenses that preserve attribution can improve reputation and awareness of your work. Using open document formats for collaboration creates positive feedback to improve free productivity tools, which will lead to lower costs in the long run.
There is much more to be said on this topic, here and elsewhere. Democratization of science is something that I think about daily and is an ideal that I strive to uphold in my own research as much as I am able.