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How Does National Scientific Funding Support Emerging Interdisciplinary Research: A Comparison Study of Big Data Research in the US and China

机译:国家科学资助如何支持新兴的跨学科研究:中美大数据研究的比较研究

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摘要

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.
机译:资助机构如何增强其能力以支持快速发展的领域中的研究?本文通过比较美国国家科学基金会(NSF)和中国国家自然科学基金会(NSFC)在大数据领域的研究建议来解决这个问题。大数据的特点是其大小以及在合理的时间段内难以捕获,管理,管理和处理它。尽管大数据在长期的信息技术研究中具有悠久的历史,但该领域在短时间内发展非常迅速。我们发现,跨学科的程度是这些资助机构如何应对大数据崛起的关键方面。我们的结果表明,两个机构都能够调拨资金来支持多个领域的大数据研究,但NSF在很大程度上依赖于来自不同领域的多项目资金。我们讨论了这些跨学科方法如何反映这两个国家的研究热点和创新途径。

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