With greater public access, scientific articles are expected to reach a broader audience, generating a broader scope of creativity and inspiration and likely leading to more and faster follow-on research. This project empirically investigates the effects of greater public accessibility to scientific publications resulting from federally funded research on knowledge flow and diffusion in both academic and industrial research. The project focuses on the National Institutes of Health (NIH) Public Access Policy, effective in April 2008, that requires NIH awardees to make peer-reviewed publications resulting from NIH-funded research publically available free of charge in PubMed Central (PMC) within twelve months after the original publication. Employing expertise in economics, computer sciences and the biosciences, this research analyzes changes in (1) paper citation networks to uncover the impacts of the NIH policy on knowledge diffusion in academic research, and (2) heterogeneous paper and patent citation networks to understand the effects of the policy on industrial research. The project proposes and verifies various measures of degree, breadth and speed of knowledge flow on citation networks, and develops novel citation network growth models that are useful for policy scenario analyses.
The White House Office of Science and Technology Policy (OSTP) recently issued a memorandum to Federal agencies with more than $100 million in research and development expenditure, directing them to develop plans to increase public accessibility to results and data of federally-funded research. Some other governments have implemented or considered similar policies. This research sheds urgently-needed empirical lights on whether such policies are likely to achieve the overarching goals including accelerating the progress of science, spurring innovation and stimulating economic growth. It provides empirical results and insights for 'evidence-based' policy making on this important science and innovation policy. The analytical frameworks, methodologies and algorithms developed in this project are valuable for evaluation of similar or related policy initiatives in the future.
|Effective start/end date
|6/1/14 → 5/31/18
- National Science Foundation: $619,768.00