Research on the Science and Technology Enterprise: Indicators, Statistics, and Methods (NCSES S&T)
NSF 21-627 https://www.nsf.gov/pubs/2021/nsf21627/nsf21627.htm
National Science Foundation Directorate for Social, Behavioral and Economic Sciences
Standard research proposals and Doctoral Dissertation Research Improvement Grant (DDRIG) proposals are submitted directly to this solicitation, Research on the Science and Technology Enterprise: Indicators, Statistics, and Methods (NCSES S&T). The NCSES S&T program also supports Faculty Early Career Development (CAREER) awards and supplements for Research Experiences for Undergraduates (REU), as well as RAPID, EAGER, and conference awards. Please see the applicable program solicitation or the PAPPG for additional information.
The National Center for Science and Engineering Statistics (NCSES) of the National Science Foundation (NSF) is responsible for the collection, acquisition, analysis, reporting and dissemination of objective, statistical data related to the science and technology (S&T) enterprise in the United States and other nations that is relevant and useful to practitioners, researchers, policymakers and the public. NCSES uses this information to prepare a number of statistical data reports including Women, Minorities and Persons with Disabilities in Science and Engineering and the National Science Board's biennial report, Science and Engineering (S&E) Indicators.
The Center would like to enhance its efforts to support analytic and methodological research in support of its surveys as well as promote the education and training of researchers in the use of large-scale nationally representative datasets. NCSES welcomes efforts by the research community to use NCSES or other data to conduct research on the S&T enterprise, develop improved survey methodologies that could benefit NCSES surveys, explore alternate data sources that could supplement NCSES data, create and improve indicators of S&T activities and resources, strengthen methodologies to analyze S&T statistical data, and explore innovative ways to communicate S&T statistics.