Integration and Implementation Insights

Reinventing science? From open source to open science

By Alexey Voinov

alexey voinov
Alexey Voinov (biography)

Science is getting increasingly bureaucratized, more and more driven by metrics and indices, which have very little to do with the actual scientific content and recognition among peers. This is actively supported by the still dominant for-profit publication mechanism, which harvests products of scientific research for free, processes, reviews and edits them using voluntary work of scientists themselves and then sells the resulting papers back to the scientific community at obscene costs. The original ideals of scientific pursuit of truth for the sake of the betterment of humanity are diluted and forfeited in the exhausting race for grants, tenure, patents, citations and nominations. Something has to change, especially in the era of post-normal science when so much is at stake, and so little is actually done to address the mounting problems of the environment and society.

In computer programming open source emerged in the 1980s largely in opposition to attempts at licensing code and the growing dominance of Windows with the annoyingly secretive policies of Microsoft. It came as the idealistic philosophy of software development that stems from the so-called “gift culture” and “gift economy” based on this culture. Under gift culture you gain status and reputation, not by possessing things or ideas other people want, not by occupying a dominant or special position, but rather by of giving your time, your creativity, and the results of your skill. Some of the best known off-springs of the open source paradigm are the first web browsers that helped the Internet to happen (Mosaic, Apache, Mozilla, etc.) and the Linux operating system.

Gift culture, and the dedicated protection of a free intellectual commons, is a powerful incentive that seems to be most appropriate for the scientific pursuit in general, not just computer engineering and programing. While some federal and international agencies already require open source delivery of code and data as a funding prerequisite, there is also a growing trend towards ‘open access’ for the scientific publications that result from federally funded research.

We need to promote a shift in the traditional reward system for scientific research. While individual efforts and talent drive science, we have reached a point where team efforts are required for most breakthrough achievements. While gift culture is inherent to the scientific community, it has been significantly compromised by privatization of science and severe competition for diminishing resources. It is paramount to reaffirm our commitment to the fundamental precepts of science and encourage the rebuilding of a culture of collaboration and information sharing.

However the shift to ‘open science’ that would be based on the same paradigms as ‘open source’, and would support transparency and inclusiveness, not just for the results of research but for the research process itself, is yet to be achieved. It will be hard to adopt this approach due to competing pressures or simply excuses that results are intellectual property, the student has not graduated yet, the paper is not yet accepted, code is clumsy, documentation is not complete, or that a few more tests or fixes need to be made…. Academic institutions are also to blame, as they look to the commercialization and patenting of faculty-conducted research as source of income to enhance University revenues.

It would also be helpful if we could shift some emphasis away from peer-reviewed publications toward less traditional products like well-documented models, data and code. More appreciation should be given to the reviewers themselves by acknowledging their efforts and giving them credit. Journals should encourage open, collaborative reviewing rather than blind reviews that breed competition and suppression of new ideas. There is an obvious need for new award and credit systems that would stimulate sharing and teamwork rather than direct personal gain. Again there is much to learn from the experience in licensing that is available from the open source community.

The development of appropriate supporting infrastructure, licenses and standards can certainly affect the collaborative behavior of participants. There is evidence for this in how infrastructure for user-generated content has revolutionized development and access to information through social networks, in efforts like Wikipedia and Myspace. Here again there is much to learn from the open source community. At the same time there is clear evidence that the reward system for research is already changing. The Nobel Prize awarded to the Intergovernmental Panel on Climate Change (IPCC) team is probably the first time such a large group was acknowledged, and is a tangible indicator that some challenging science questions are now inaccessible without huge teams that work in collaboration.

Funding agencies could certainly help by further supporting and encouraging community research, but this may take a long time. The model adopted by SESYNC is unique and holds much promise. It already largely depends on voluntary contributions of scientists, who do all the work on their own, at their own cost, with support provided only for communication – remotely through web services, and in-person during a small number of meetings with travel paid for.

What other initiatives are out there that could be built on?

The post is based on some ideas that previously appeared in:
Voinov, A.A., et al., (2010). A Community Approach to Earth Systems Modeling. EOS, Transactions. American Geophysical Union, 91, 13: 117–124.

Voinov, Alexey. (2008). Systems Science and Modeling for Ecological Economics. Academic Press (Chapter 9).

Biography: Alexey Voinov PhD is Professor of Spatio-Temporal Systems Modeling for Sustainability Science at the University of Twente Faculty for Geo-information Science and Earth Observation in the Netherlands. His academic and teaching interests evolve around spatial dynamic modeling of ecosystems and sustainability science in application to decision support and policy making. In particular he is interested in integrated modeling and participatory modeling, integrated assessment, systems analysis in ecology and economics, energy and natural resources, with applications in watershed management, agroecology, energy policy. He is a keen advocate of stakeholder involvement in modeling and decision making. He is a Principal Investigator of the Participatory Modeling Pursuit funded by the National Socio-Environmental Synthesis Center (SESYNC).

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