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The past 50 years have witnessed a revolution in computing and related communications technologies. The contributions of industry and university researchers to this revolution are manifest; less widely recognized is the major role the federal government played in launching the computing revolution and sustaining its momentum. Funding a Revolution examines the history of computing since World War II to elucidate the federal government's role in funding computing research, supporting the education of computer scientists and engineers, and equipping university research labs. It reviews the economic rationale for government support of research, characterizes federal support for computing research, and summarizes key historical advances in which government-sponsored research played an important role. Funding a Revolution contains a series of case studies in relational databases, the Internet, theoretical computer science, artificial intelligence, and virtual reality that demonstrate the complex interactions among government, universities, and industry that have driven the field. It offers a series of lessons that identify factors contributing to the success of the nation's computing enterprise and the government's role within it.
Federal government statistics provide critical information to the country and serve a key role in a democracy. For decades, sample surveys with instruments carefully designed for particular data needs have been one of the primary methods for collecting data for federal statistics. However, the costs of conducting such surveys have been increasing while response rates have been declining, and many surveys are not able to fulfill growing demands for more timely information and for more detailed information at state and local levels. Innovations in Federal Statistics examines the opportunities and risks of using government administrative and private sector data sources to foster a paradigm shift in federal statistical programs that would combine diverse data sources in a secure manner to enhance federal statistics. This first publication of a two-part series discusses the challenges faced by the federal statistical system and the foundational elements needed for a new paradigm.
Includes testimony by Susan Kladiva, GAO. Discusses the dist. of awards, with special emphasis on the 25 co's. that have won the most awards. Discusses commercial potential as a factor taken into consideration by Fed. agencies when evaluating co's'. proposals. Includes a matter that may help to clarify the relative emphasis that agencies, in evaluating proposals, should give to a company's commercialization record as part of the goal of commercialization & to the program's other goals. Contains a recommendation that may help to strengthen the evaluation of the program's commercial outcomes in response to the Gov't. Performance & Results Act.
Two surveys of the National Science Foundation's Division of Science Resources Statistics (SRS) provide some of the most significant data available to understand research and development spending and policy in the United States. These are the Survey of Federal Funds for Research and Development and the Survey of Federal Science and Engineering Support to Universities, Colleges, and Nonprofit Institutions. These surveys help reach conclusions about fundamental policy questions, such as whether a given field of research is adequately funded, whether funding is balanced among fields, and whether deficiencies in funding may be contributing to a loss of U.S. scientific or economic competitiveness. However, the survey data are of insufficient quality and timeliness to support many of the demands put on them. In addition the surveys are increasingly difficult to conduct in times of constrained resources, and their technological, procedural, and conceptual infrastructure has not been modernized for procedure or content. Data on Federal Research and Development Investments reviews the uses and collection of data on federal funds and federal support for science and technology and recommends future directions for the program based on an assessment of these uses and the adequacy of the surveys. The book also considers the classification structure, or taxonomy, for the fields of science and engineering.