![]() surveys: “Threatened coverage of frames falling participation rates increasing reliance on nonresponse adjustments and for surveys with high response rate targets, inflated costs.” His proposed solution for agencies to address these issues is to develop an approach of a “blended data world by building on top of existing surveys.” 1 Groves (2011b) envisions multimodal data acquisition and manipulation of data, including “Internet behaviors administrative records Internet self-reporting telephone, face-to-face, paper surveys real-time mode switch to fill in missing data and real-time estimation.” 2 In his November 2011 presentation at the annual meeting of the Consortium of Social Science Associations, Robert Groves (2011a) conveyed the status of U.S. These tools provide information much more rapidly than is possible with traditional surveys, which entail up to multiple-year lags. ![]() The World Wide Web, in particular, has been transformational in enabling new forecasting and data collection methods that yield useful insights in almost real time. NCSES and, indeed, other government statistical agencies confront a world of dizzying change in the way information technology is integrated into their data-gathering and data-management activities. The North American Industry Classification System (NAICS) codes and the Standard Occupational Codes may also undergo revision within the next decade. The group plans to work on priority themes and to build a better bridge between the two manuals. OECD’s National Experts on Science and Technology Indicators are revising the Frascati Manual (OECD, 2002) and the Oslo Manual (OECD-Eurostat, 2005) on a rolling basis. Standards and taxonomies for data collection and analysis are expected to change before the end of this decade. This chapter explores this changing landscape of data collection and analysis and its implications for NCSES’s STI indicators program. Users have rising expectations, and they are demanding more access to statistics that are closer to actual measures of what they want to know.Sources of knowledge generation and innovation are expanding beyond developed countries to emerging and developing economies.Repositories of STI measures that users demand are distributed among several statistical agencies and private repositories.Tools for data extraction, manipulation, and analysis are evolving rapidly.As discussed in previous chapters, traditional surveys face increasing expense, declining response rates (Williams, 2013), and lengthy time lags between when data are gathered and when derived indicators and other statistics can be published.The agency’s science, technology, and innovation (STI) indicators program must deal with several challenges: The National Center for Science and Engineering Statistics (NCSES) finds itself in the midst of a paradigm shift in the way data are gathered, manipulated, and disseminated. A Paradigm Shift in Data Collection and Analysis
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