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

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.

Ethical use of animal models in musculoskeletal research

“…With the move toward the era of large interdisciplinary research teams and "big science," there is a much greater emphasis on inter-disciplinary teamwork in research. 15 As a result, it is commonplace to see investigators from engineering, cell biology, and medicine working together on an experimental study. There are clear benefits to the development of this team-based approach, but it also creates challenges, especially with regard to experience in, and attitudes toward, animal research.…”

Text Mining Transportation Research Grant Big Data: Knowledge Extraction and Predictive Modeling Using Fast Neural Nets

“…Moreover, the analysis was limited to a short period (i.e., 2000-2003) for the information technolog y European program. In the recent times, the analysis is done on publically available databases such as those from National Institutes of Health (NIH) (Talley et al, 2011;Park et al, 2016), National Science Foundation (NSF), and The National Natural Science Foundation of China (NSFC) (Huang et al, 2016). Park et al, (2016) performed analysis on the NIH database that revealed several insights about funding investment patterns in various diseases.…”

“…Park et al, (2016) performed analysis on the NIH database that revealed several insights about funding investment patterns in various diseases. Huang et al, (2016) provided a comparative study of NSF and NSFC in the field of Big Data. Their main finding explained how these agencies address the need of big data by focusing on interdisciplinary research projects.…”

National Scientific Funding for Interdisciplinary Research: A Comparison Study of Infectious Diseases in the US and EU

“…Namely, it is inappropriate to use publications or patents to establish future-oriented strategies. As a consequence, prominent scholars have emphasised the utilisation of funding data as an alternative [20,21]. Although research based on funding was conducted, its focus was not the investigation of a disciplinary approach, but the distribution of funding for infectious diseases [22].…”