Science and Engineering Indicators (SEI) is first and foremost a volume of record comprising the major high-quality quantitative data on the U.S. and international science and engineering enterprise. SEI is factual and policy neutral. It doesn’t offer policy options, and it doesn’t make policy recommendations. SEI employs a variety of presentation styles—tables, figures, narrative text, bulleted text, Web- based links, highlights, introductions, conclusions and reference lists—to make the data accessible to readers with different information needs and different information-processing preferences.
The data are “indicators.” Indicators are quantitative representations that might reasonably be thought to provide summary information bearing on the scope, quality and vitality of the science and engineering enterprise. The indicators reported in SEI are intended to contribute to an understanding of the current environment and to inform the development of future policies. SEI does not model the dynamics of the science and engineering enterprise, and it avoids strong claims about the significance of the indicators it reports. SEI is used by readers who hold a variety of views about which indicators are most significant for different purposes.
SEI is prepared by the National Science Foundation’s National Center for Science and Engineering Statistics (NCSES) under the guidance of the National Science Board (Board). It is subject to extensive review by outside experts interested federal agencies, Board members and NSF internal reviewers for accuracy, coverage and balance.
SEI includes more information about measurement than many readers unaccustomed to analyzing social and economic data may find easy to absorb. This information is included because readers need a good understanding of what the reported measures mean and how the data were collected in order to use the data appropriately. SEI’s data analyses, however, are relatively accessible. The data can be examined in various ways, and SEI generally emphasizes neutral, factual description and avoids unconventional or controversial analysis. As a result, SEI almost exclusively uses simple statistical tools that should be familiar and accessible to a college bound high school graduate. Readers comfortable with numbers and percentages and equipped with a general conceptual understanding of terms such as “statistical significance” and “margin of error” will readily understand the statistical material in SEI. A statistical appendix aids readers’ interpretation of the material presented.
Source: National Science Foundation