NSF urges lawmakers to back use of better science data

The National Science Foundation wants Members of Congress to support its efforts to collect and assess interdisciplinary data to determine the effectiveness of scientific policy, known as the Science of Science Policy.

Rep. Daniel Lipinski (D-Ill.), who chairs the House Science and Technology Committee's Research and Scientific Education Subcommittee, called witnesses to testify about the NSF’s approach at a hearing Sept. 23.

“The best policies are not self-evident,” Lipinski said. “As someone who was trained as an engineer and a social scientist, I believe we need data and proper analysis of this data to be able to determine – as best we can – the optimal policy to implement.”

The NSF created the Office of Science of Science and Innovation Policy in 2005 to develop better tools to weigh the effects of science policy decisions on science, innovation and research.

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The White House Office of Science and Technology Policy, along with NSF and the National Institutes of Health, launched the “Star Metrics” program in June to measure the effects of federal research spending on innovation, competitiveness and science. NSF and the national institutes committed $1 million to the program for its first year.

Julia Lane, program director for NSF’s Science of Science and Innovation Policy program, said the program’s goals are to advance evidence-based decision-making, build a scientific community to study science and innovation policy, and develop improved data.

The “science of science policy” field of research is broad, interdisciplinary and flexible, and must be able to change direction and cross boundaries, Lane testified. At the same time, scientists’ lack of agreement on basic definitions and boundaries appears to be hampering analysis, she said.

“The lack of analytical capacity in science policy is in sharp contrast to other policy fields that focus on workforce, health and education,” Lane said. “Each of those efforts, however, has benefited from an understanding of the systems that are being analyzed. In the case of science policy, no such agreement currently exists.”

Also, public understanding about the value of scientific research to society has operated under several general principles being challenged by today’s economic situation, said Daniel Sarewitz, co-director of the Consortium for Science Policy and Outcomes at Arizona State University.

One popular belief is that spending more on research creates more positive outcomes, and another is that research spending delivers results in a linear fashion. There are also common beliefs about distinctions between pure research and applied research, and about the peer review process as the best indicator of the quality and value of the research, he added.

New assessment models are needed for the future, Sarewitz said.

“In an era of constrained resources and mounting challenges to our well-being, the limits of the input-output approach become impossible to ignore,” Sarewitz said.