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Interdisciplinarity research based on NSFC-sponsored projects: A case study of mathematics in Chinese universities.


ABSTRACT: We investigate the interdisciplinarity of mathematics based on an analysis of projects sponsored by the NSFC (National Natural Science Foundation of China). The motivation of this study lies in obtaining an efficient method to quantify the research interdisciplinarities, revealing the research interdisciplinarity patterns of mathematics discipline, giving insights for mathematics scholars to improve their research, and providing empirical supports for policy making. Our data set includes 6147 NSFC-sponsored projects implemented by 3225 mathematics professors in 177 Chinese universities with established mathematics departments. We propose the weighted-mean DIRD (diversity of individual research disciplines) to quantify interdisciplinarity. In addition, we introduce the matrix computation method, discover several properties of such a matrix, and make the computation cost significantly lower than the bitwise computation method. Finally, we develop an automatic DIRD computing system. The results indicate that mathematics professors at top normal universities in China exhibit strong interdisciplinarity; mathematics professors are most likely to conduct interdisciplinary research involving information science (research department), computer science (research area), computer application technology (research field), and power system bifurcation and chaos (research direction).

SUBMITTER: Shao ZY 

PROVIDER: S-EPMC6067728 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Interdisciplinarity research based on NSFC-sponsored projects: A case study of mathematics in Chinese universities.

Shao Zhi-Yi ZY   Li Yong-Ming YM   Hui Fen F   Zheng Yang Y   Guo Ying-Jie YJ  

PloS one 20180731 7


We investigate the interdisciplinarity of mathematics based on an analysis of projects sponsored by the NSFC (National Natural Science Foundation of China). The motivation of this study lies in obtaining an efficient method to quantify the research interdisciplinarities, revealing the research interdisciplinarity patterns of mathematics discipline, giving insights for mathematics scholars to improve their research, and providing empirical supports for policy making. Our data set includes 6147 NS  ...[more]

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