Search

The Materials Genome Initiative (MGI) was launched in 2011 by the White House Office of Science and Technology Policy to help accelerate the design, discovery, development and deployment of advanced materials and to reduce costs through the integration of advanced computation and data management with experimental synthesis and characterization. A broad range of federal agencies - including the National Science Foundation (NSF), the Department of Energy, and the Department of Defense - are part of the MGI effort and have invested more than $1 billion in resources and infrastructure accumulative since the start. The efforts of NSF have been focused largely within the Designing Materials to Revolutionize and Engineer Our Future (DMREF) program, which supports the development of fundamental science, computational and experimental tools for generating and managing data, and workforce that enable industry and other government agencies to develop and deploy materials that meet societal needs and national priorities. At the request of NSF, this report evaluates the goals, progress, and scientific accomplishments of the DMREF program within the context of similar efforts both within the United States and abroad. The recommendations of this report will assist NSF as it continues to increase its engagement with industry and federal agencies to transition the results from fundamental science efforts to reach the MGI goal of deploying advanced materials at least twice as fast as possible today, at a fraction of the cost that meet national priorities.

The Antarctic's unique environment and position on the globe make it a prime location to gain insights into how Earth and the universe operate. This report assesses National Science Foundation (NSF) progress in addressing three priority research areas identified in a 2015 National Academies report: (1) understanding the linkages between ice sheets and sea-level rise, including both a focus on current rates of ice sheet change and studies of past major ice sheet retreat episodes; (2) understanding biological adaptations to the extreme and changing Antarctic environment; and (3) establishing a next-generation cosmic microwave background (CMB) program, partly located in Antarctica, to study the origins of the universe. NSF has made important progress understanding the impacts of current ice sheet change, particularly through studies focused on the ice sheet and ocean interactions driving ongoing ice mass loss at the Thwaites Glacier and Amundsen Sea region in West Antarctica. Less progress has been made on studies of past major ice sheet retreat episodes. Progress is also strong on CMB research to understand the origins of the universe. Progress has lagged on understanding biological adaptations, in part because of limited community organization and collaboration toward the priority. To accelerate progress during the second half of the initiative, NSF could issue specific calls for proposals, develop strategies to foster collaborations and partnerships, and commission a transparent review of logistical capacity to help illuminate strategies and priorities for addressing resource constraints. Such efforts would also help optimize science and proposal development in an environment of inherently constrained logistics.

Convergence has been a key topic of discussion about the future of cyberinfrastructure for science and engineering research. Convergence refers both to the combined use of simulation and data-centric techniques in science and engineering research and the possibilities for a single type of cyberinfrastructure to support both techniques. The National Academies of Science, Engineering, and Medicine convened a Workshop on Converging Simulation and Data-Driven Science on May 10, 2018, in Washington, D.C. The workshop featured speakers from universities, national laboratories, technology companies, and federal agencies who addressed the potential benefits and limitations of convergence as they relate to scientific needs, technological capabilities, funding structures, and system design requirements. This publication summarizes the presentations and discussions from the workshop.

Advanced computing capabilities are used to tackle a rapidly growing range of challenging science and engineering problems, many of which are compute- and data-intensive as well. Demand for advanced computing has been growing for all types and capabilities of systems, from large numbers of single commodity nodes to jobs requiring thousands of cores; for systems with fast interconnects; for systems with excellent data handling and management; and for an increasingly diverse set of applications that includes data analytics as well as modeling and simulation. Since the advent of its supercomputing centers, the National Science Foundation (NSF) has provided its researchers with state-of-the-art computing systems. The growth of new models of computing, including cloud computing and publically available by privately held data repositories, opens up new possibilities for NSF. In order to better understand the expanding and diverse requirements of the science and engineering community and the importance of a new broader range of advanced computing infrastructure, the NSF requested that the National Research Council carry out a study examining anticipated priorities and associated tradeoffs for advanced computing. Future Directions for NSF Advanced Computing Infrastructure to Support U.S. Science and Engineering in 2017-2020 provides a framework for future decision-making about NSF's advanced computing strategy and programs. It offers recommendations aimed at achieving four broad goals: (1) position the U.S. for continued leadership in science and engineering, (2) ensure that resources meet community needs, (3) aid the scientific community in keeping up with the revolution in computing, and (4) sustain the infrastructure for advanced computing.

Ocean science connects a global community of scientists in many disciplines - physics, chemistry, biology, geology and geophysics. New observational and computational technologies are transforming the ability of scientists to study the global ocean with a more integrated and dynamic approach. This enhanced understanding of the ocean is becoming ever more important in an economically and geopolitically connected world, and contributes vital information to policy and decision makers charged with addressing societal interests in the ocean. Science provides the knowledge necessary to realize the benefits and manage the risks of the ocean. Comprehensive understanding of the global ocean is fundamental to forecasting and managing risks from severe storms, adapting to the impacts of climate change, and managing ocean resources. In the United States, the National Science Foundation (NSF) is the primary funder of the basic research which underlies advances in our understanding of the ocean. Sea Change addresses the strategic investments necessary at NSF to ensure a robust ocean scientific enterprise over the next decade. This survey provides guidance from the ocean sciences community on research and facilities priorities for the coming decade and makes recommendations for funding priorities.

Advanced computing capabilities are used to tackle a rapidly growing range of challenging science and engineering problems, many of which are compute- and data-intensive as well. Demand for advanced computing has been growing for all types and capabilities of systems, from large numbers of single commodity nodes to jobs requiring thousands of cores; for systems with fast interconnects; for systems with excellent data handling and management; and for an increasingly diverse set of applications that includes data analytics as well as modeling and simulation. Since the advent of its supercomputing centers, the National Science Foundation (NSF) has provided its researchers with state-of-the-art computing systems. The growth of new models of computing, including cloud computing and publically available by privately held data repositories, opens up new possibilities for NSF. In order to better understand the expanding and diverse requirements of the science and engineering community and the importance of a new broader range of advanced computing infrastructure, the NSF requested that the National Research Council carry out a study examining anticipated priorities and associated tradeoffs for advanced computing. This interim report identifies key issues and discusses potential options. Future Directions for NSF Advanced Computing Infrastructure to Support U.S. Science and Engineering in 2017-2020 examines priorities and associated tradeoffs for advanced computing in support of NSF-sponsored science and engineering research. This report is an initial compilation of issues to be considered as future NSF strategy, budgets, and programs for advanced computing are developed. Included in the report are questions on which the authoring committee invites comment. We invite your feedback on this report, and more generally, your comments on the future of advanced computing at NSF.

The National Science Foundation (NSF) has long collected information on the number and characteristics of individuals with education or employment in science and engineering and related fields in the United States. An important motivation for this effort is to fulfill a congressional mandate to monitor the status of women and minorities in the science and engineering workforce. Consequently, many statistics are calculated by race or ethnicity, gender, and disability status. For more than 25 years, NSF obtained a sample frame for identifying the target population for information it gathered from the list of respondents to the decennial census long-form who indicated that they had earned a bachelors or higher degree. The probability that an individual was sampled from this list was dependent on both demographic and employment characteristics. But, the source for the sample frame will no longer be available because the census long-form is being replaced as of the 2010 census with the continuous collection of detailed demographic and other information in the new American Community Survey (ACS). At the request of NSF's Science Resources Statistics Division, the Committee on National Statistics of the National Research Council formed a panel to conduct a workshop and study the issues involved in replacing the decennial census long-form sample with a sample from the ACS to serve as the frame for the information the NSF gathers. The workshop had the specific objective of identifying issues for the collection of field of degree information on the ACS with regard to goals, content, statistical methodology, data quality, and data products.

This book reviews the evaluation research literature that has accumulated around 19 K-12 mathematics curricula and breaks new ground in framing an ambitious and rigorous approach to curriculum evaluation that has relevance beyond mathematics. The committee that produced this book consisted of mathematicians, mathematics educators, and methodologists who began with the following charge: Evaluate the quality of the evaluations of the thirteen National Science Foundation (NSF)-supported and six commercially generated mathematics curriculum materials; Determine whether the available data are sufficient for evaluating the efficacy of these materials, and if not; Develop recommendations about the design of a project that could result in the generation of more reliable and valid data for evaluating such materials. The committee collected, reviewed, and classified almost 700 studies, solicited expert testimony during two workshops, developed an evaluation framework, established dimensions/criteria for three methodologies (content analyses, comparative studies, and case studies), drew conclusions on the corpus of studies, and made recommendations for future research.

In 1995, the National Science Foundation (NSF) created a special account to fund large (several tens of millions of dollars) research facilities. Over the years, these facilities have come to represent an increasingly prominent part of the nation's R&D portfolio. Recently concern has intensified about the way NSF is selecting projects for this account. In 2003, six U.S. Senators including the chair and ranking member of the Senate Subcommittee on VA, HUD, and Independent Agencies Appropriations expressed these concerns in a letter to the NRC asking it to'review the current prioritization process and report to us on how it can be improved.'This report presents a series of recommendations on how NSF can improve its priority setting process for large research facilities. While noting that NSF has improved this process, the report states that further strengthening is needed if NSF is to meet future demands for such projects.

The science and engineering enterprise has continued to evolve, responding over the last decade to increased economic globalization, a post-cold war military, federal budget fluctuations, and structural changes in the way science and engineering are conducted and innovations are adopted. This report suggests ways to revise the data collection activities of the Science Resources Studies Division (SRS) of the National Science Foundation to better capture the current realities of R&D funding and S&E human resources. The report's recommendations would improve the relevance of the data on graduate education, the labor market for scientists and engineers, and the funding and conduct of research and development, and thus better meet the data needs of policymakers, managers, and researchers.

As part of its mission to foster high-quality scientific and engineering research, the National Science Foundation (NSF) plans, grants, and administers major awards to universities and other research institutions for national research facilities, multidisciplinary research centers, and other large-scale research projects. Although few in number, less than 100, such projects account for about 30 percent of NSF's annual research budget. This book provides a useful overview of how such projects are planned, reviews proposals for merit, and evaluates ongoing projects for renewal awards. The panel makes a series of recommendations for strengthening major award decisionmaking.