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A New Map of Science
Better metrics and a more robust cyberinfrastructure can be powerful tools for promoting science transfer, but they will require skilled people to wield them. Computer systems that draw connections between discrete chunks of information show the promise of semantic networks—whether these systems are ambitious, all-encompassing “knowledge engines” like Wolfram Alpha or purely commercial projects like Netflix’s algorithm for measuring and predicting the viewing preferences of its customers. But even these successes readily reveal the limits of automation.
Wolfram Alpha excels at connecting information in unrelated mathematical databases. Inputting a volume in milliliters provides a list of unit conversions, but it also yields comparisons to food portions and the lung capacity of a typical human. However, comparisons outside the realm of mathematics remain elusive; the public-sphere problems that science transfer could help inform and solve aren’t easily distilled into mathematical variables and equations. Whether it is knowing how the geographic distribution of grocery stores and fast-food chains affects obesity rates, or what sorts of incentives cause people to most drastically reduce their carbon footprint, even first defining the parameters of the problem requires qualitative, rather than quantitative, approaches.
Even if we erect massive databases filled with information on how scientific work is being used in real time, for the foreseeable future it seems inescapable that humans must provide oversight to derive actionable knowledge from the data. Modern weather forecasting provides an illustrative example: Copious real-time data on world weather patterns is available to anyone with a computer and an internet connection, but the vast majority of us rely on meteorologists to synthesize and analyze it to produce a daily forecast. Moreover, even more raw data and subsequent analysis are necessary to transform information about weather into knowledge about climate and how human activity has influenced it over the course of centuries.
Well-designed computer programs may be able to compile usage data on scientific discourse and publishing to generate real-time maps of scientific activity, but such maps can only inform our decision making, not replace it. A new skill set that makes use of such tools—a kind of “science meteorology”—will be necessary to serve as a bridge between the academic and public spheres.
This practice will have a number of disciplinary forebears, including those who have worked in fields such as science and technology studies (STS), the history and philosophy of science, and even the specialized branches of information science that produce bibliometricians. But unlike historians and philosophers of science, practicioners of this new discipline will emphasize the present and future much more than the past.
Though informed by the theoretical analysis of past events and the factors that led to their development, this new breed of specialist will be chiefly concerned with applied techniques for measuring and shaping dynamic evolving situations. They will track how scientists relate new information to policymakers and the public and gauge how this information is then assimilated. They will quantify risks related to supporting new emerging scientific disciplines and manage expectations for potential rewards. They will bring much-needed self-awareness to the endeavor of science.
The nature of their practice would necessarily differ from that of typical bench scientists; even if these specialists were educated and trained in university STS departments, it would be impossible to confine them to one disciplinary silo. This new discipline must be organized in a way that is perpendicular to the vertical structures of academic departments. Interdisciplinary work with scientists in every subfield of the physical and social sciences, as well as with journalists, policymakers, educators, and others, will be the norm, rather than the exception.
Fortunately, creating opportunities for this new discipline to work in a horizontal fashion is in itself a step in the right direction. An interdisciplinary approach is necessary for the weighty, interconnected problems—from sustainable development to climate change—that are most in need of science transfer. And bringing scientists and their ideas together is a dependable way of generating new ideas, sometimes of the world-changing variety. Whether convening in physical space, as with the national laboratories at Oak Ridge and Los Alamos for the Manhattan Project, or virtually, with the myriad forms of online communication that increasingly make up the day-to-day practice of science, new connections can mean new ways of thinking.
A new breed of interdisciplinary research centers could be the breeding ground for science meteorology. Organized around public-sphere problems rather than convergent branches of science, and sometimes existing outside the bounds of academia altogether, these institutions are in some ways more akin to public policy think tanks than university departments. There is, of course, one key difference: At such institutions, policy is developed symbiotically and synergistically with original scientific research.
Places like Columbia University’s Earth Institute and the Stockholm Resilience Centre bring together individuals with backgrounds in geophysics, biochemistry, and the social sciences to address problems in ecological sustainability and development. The Earth Institute’s 16 research units and 14 educational programs are staffed by Columbia faculty, drawing from its science departments, as well as its schools of law, business, and international politics.
Christine Alfsen-Norodom, an officer of the United Nations’ Educational, Scientific, and Cultural Organization (UNESCO), has worked with both organizations to promote sustainable development. “After 20 years advising governments on natural resource management, what I thought was missing was a conceptual, theoretical underpinning of what I was doing,” says Alfsen-Norodom. “I would get that from high-ranking consultants, from time to time, but I felt that I needed a more constant source of discussion of research feeding into my work. Something on a systematic basis rather than just hiring a consultant on occasion.”
That perspective led Alfsen-Norodom to partner with the Earth Institute with the Columbia University/UNESCO Joint Program on Biosphere and Society (CUBES). The partnership showed the advantages of such interdisciplinary collaboration, but it also revealed the hurdles that have slowed their formation. “The policy-normative agencies, like the UN, and the scientific agencies, like universities, are completely different animals that are not meant to communicate with one another from a structural point of view. It takes a lot of work to fix the scale mismatch,” says Alfsen-Norodom. “Operating in the middle has a cost, professionally. For the university people, it means they are publishing less in their field. For policy people like me, because you’re stepping out of your line of work and spending so much time talking to others, sometimes you’re perceived as not working for your own organization.”
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