How Does National Scientific Funding Support Emerging Interdisciplinary Research: A Comparison Study of Big Data Research in the US and China
Identifieur interne : 000028 ( Main/Exploration ); précédent : 000027; suivant : 000029How Does National Scientific Funding Support Emerging Interdisciplinary Research: A Comparison Study of Big Data Research in the US and China
Auteurs : Ying Huang [République populaire de Chine] ; Yi Zhang [République populaire de Chine, Australie] ; Jan Youtie [États-Unis] ; Alan L. Porter [États-Unis] ; Xuefeng Wang [République populaire de Chine]Source :
- PLoS ONE [ 1932-6203 ] ; 2016.
Abstract
How do funding agencies ramp-up their capabilities to support research in a rapidly emerging area? This paper addresses this question through a comparison of research proposals awarded by the US National Science Foundation (NSF) and the National Natural Science Foundation of China (NSFC) in the field of Big Data. Big data is characterized by its size and difficulties in capturing, curating, managing and processing it in reasonable periods of time. Although Big Data has its legacy in longstanding information technology research, the field grew very rapidly over a short period. We find that the extent of interdisciplinarity is a key aspect in how these funding agencies address the rise of Big Data. Our results show that both agencies have been able to marshal funding to support Big Data research in multiple areas, but the NSF relies to a greater extent on multi-program funding from different fields. We discuss how these interdisciplinary approaches reflect the research hot-spots and innovation pathways in these two countries.
Url:
DOI: 10.1371/journal.pone.0154509
PubMed: 27219466
PubMed Central: 4878788
Affiliations:
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Porter</name><affiliation wicri:level="1"><nlm:aff id="aff004"><addr-line>School of Public Policy, Georgia Institute of Technology, Atlanta, GA, 30332, United States of America</addr-line></nlm:aff><country xml:lang="fr">États-Unis</country><wicri:regionArea>School of Public Policy, Georgia Institute of Technology, Atlanta, GA, 30332</wicri:regionArea><wicri:noRegion>30332</wicri:noRegion></affiliation></author><author><name sortKey="Wang, Xuefeng" sort="Wang, Xuefeng" uniqKey="Wang X" first="Xuefeng" last="Wang">Xuefeng Wang</name><affiliation wicri:level="1"><nlm:aff id="aff001"><addr-line>School of Management and Economics, Beijing Institute of Technology, Beijing, 100081, China</addr-line></nlm:aff><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>School of Management and Economics, Beijing Institute of Technology, Beijing, 100081</wicri:regionArea><wicri:noRegion>100081</wicri:noRegion></affiliation></author></analytic><series><title level="j">PLoS ONE</title><idno type="eISSN">1932-6203</idno><imprint><date when="2016">2016</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>How do funding agencies ramp-up their capabilities to support research in a rapidly emerging area? This paper addresses this question through a comparison of research proposals awarded by the US National Science Foundation (NSF) and the National Natural Science Foundation of China (NSFC) in the field of Big Data. Big data is characterized by its size and difficulties in capturing, curating, managing and processing it in reasonable periods of time. Although Big Data has its legacy in longstanding information technology research, the field grew very rapidly over a short period. We find that the extent of interdisciplinarity is a key aspect in how these funding agencies address the rise of Big Data. Our results show that both agencies have been able to marshal funding to support Big Data research in multiple areas, but the NSF relies to a greater extent on multi-program funding from different fields. We discuss how these interdisciplinary approaches reflect the research hot-spots and innovation pathways in these two countries.</p></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Noor, A" uniqKey="Noor A">A Noor</name></author></analytic></biblStruct><biblStruct></biblStruct><biblStruct></biblStruct><biblStruct><analytic><author><name sortKey="Porter, Al" uniqKey="Porter A">AL Porter</name></author><author><name sortKey="Roessner, Jd" uniqKey="Roessner J">JD Roessner</name></author><author><name sortKey="Cohen, As" uniqKey="Cohen A">AS Cohen</name></author><author><name sortKey="Perreault, M" uniqKey="Perreault M">M Perreault</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Stirling, A" uniqKey="Stirling A">A Stirling</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Shannon, Ce" uniqKey="Shannon C">CE Shannon</name></author><author><name sortKey="Weaver, W" 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name="Australie"><noRegion><name sortKey="Zhang, Yi" sort="Zhang, Yi" uniqKey="Zhang Y" first="Yi" last="Zhang">Yi Zhang</name></noRegion></country><country name="États-Unis"><noRegion><name sortKey="Youtie, Jan" sort="Youtie, Jan" uniqKey="Youtie J" first="Jan" last="Youtie">Jan Youtie</name></noRegion><name sortKey="Porter, Alan L" sort="Porter, Alan L" uniqKey="Porter A" first="Alan L." last="Porter">Alan L. 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