Innovative Practices of Research Governance in Research Institutions Driven by Big Data

doi:10.11871/jfdc.issn.2096-742X.2024.06.005

Frontiers of Data and Computing ›› 2024, Vol. 6 ›› Issue (6): 43-52.

CSTR: 32002.14.jfdc.CN10-1649/TP.2024.06.005

doi: 10.11871/jfdc.issn.2096-742X.2024.06.005

Innovative Practices of Research Governance in Research Institutions Driven by Big Data

WANG Yang¹(),ZHOU Xiaojun¹,WEI Xin¹,CHU Dawei²,ZHENG Xiaohuan²,PENG Ying²,LENG Fuhai³,Zhang Feng³,CONG Peimin¹,JI Zhixia¹,LIAO Fangyu^1,^*()

1. Computer Network Information Center, Chinese Academy of Sciences, Beijing 100083, China
2. Chinese Academy of Sciences, Beijing 100864, China
3. Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China

Received:2024-05-06 Online:2024-12-20 Published:2024-12-20
Contact: LIAO Fangyu E-mail:wangyang@cnic.cn;fyliao@cnic.cn

Abstract

Abstract:

[Purpose] Big data-driven approaches are important tools for advancing innovation in research governance. [Methods] This paper first explores the objective factors for digital transformation of research governance, which are already in place to realize both in terms of policy and technology. Secondly, it concludes that big data-driven is the inevitable direction of research governance innovation from the process reengineering in the era of big data with “data and digital technology” as the core, and big data analysis based on “open sharing and safe and easy to use”. Finally, based on the application exploration and concrete practice of big data-driven research governance at the Chinese Academy of Sciences, this paper looks forward to the future development process of digital transformation of scientific research management institutions. [Conclusions] Big data-driven research governance innovation is a necessary path and inevitable choice to realize the modernization of research governance, which will provide strong support for China to be at the forefront of innovative countries and become a world power of scientific and technological innovation.

Key words: big data driven, research governance, governance innovation, digital technology

WANG Yang,ZHOU Xiaojun,WEI Xin,CHU Dawei,ZHENG Xiaohuan,PENG Ying,LENG Fuhai,Zhang Feng,CONG Peimin,JI Zhixia,LIAO Fangyu. Innovative Practices of Research Governance in Research Institutions Driven by Big Data[J]. Frontiers of Data and Computing, 2024, 6(6): 43-52, https://cstr.cn/32002.14.jfdc.CN10-1649/TP.2024.06.005.

Figures/Tables 3

Table 1

Index of Research Frontiers in the Biosciences in 2022[9]"

类型序号	前沿名称	研究前沿热度指数
类型序号	前沿名称	美国	中国	徳国	英国	澳大利亚
领域汇总	-	25.67	20.23	13.61	8.49	5.28
热点前沿1	ACE2以外的多个新型冠状病毒受体研究	1.65	0.39	0.67	0.61	1.08
热点前沿2	多种新型冠状病毒疫苗的研制	1.36	0.91	0.48	0.44	0.13
热点前沿3	新型冠状病毒刺突糖蛋白的结构、功能和抗原性	1.32	0.71	0.1	0.62	0.04
热点前沿4	新型冠状病毒中和抗体的发现和药物研发	1.61	0.89	0.22	0.07	0.13
热点前沿5	新型冠状病毒引发的T细胞免疫	1.34	0.35	0.89	0.36	0.29
热点前沿6	新型冠状病毒主蛋白酶的结构解析和抑制剂发现	1.16	1.8	0.07	0.53	0.73
热点前沿7	新型冠状病毒PCR核酸检测	0.27	2.28	1.49	1.54	0.05
热点前沿8	COVID-19疫情的预测模型	1.06	2.54	0.12	0.05	0.04
热点前沿9	新型冠状病毒的进化起源和中间宿主	0.87	2.24	0.42	0.05	0.84
热点前沿10	新型冠状病毒表位肽疫苗的研制	0.65	0.62	0.07	0.05	0.04
新兴前沿1	新型冠状病毒南非变异体B.1.351的抗体耐药性	1.77	0.16	0.24	0.12	0.06
新兴前沿2	新型冠状病毒巴西变异株P.1的基因组学和流行病学	2.66	0.16	2.3	1.2	0.05
新兴前沿3	AlphaFold等人工智能预测蛋白质结构	0.78	0.16	2.26	0.4	0.06
新兴前沿4	Pfam等蛋白质家族数据库	0.99	0.28	1.72	1.29	0.04
新兴前沿5	7种新型冠状病毒疫苗接种诱导的中和抗体应答	1.06	0.09	0.89	0.14	1.49
新兴前沿6	新型冠状病毒纳米颗粒疫苗诱导的中和抗体应答	1.88	0.45	1.16	0.04	0.07
新兴前沿7	小分子蛋白激酶抑制剂的理化性质	1.72	0.96	0.06	0.13	0.03
新兴前沿8	槲皮素抑制剂对新型冠状病毒主蛋白酶（Mpro）的抗病毒作用	0.3	0.43	0.07	0.15	0.01
新兴前沿9	内耳毛细胞和听觉神经元的再生和保护	0.3	0.43	0.07	0.15	0.01
新兴前沿10	新型冠状病毒感染所需宿主因子的鉴定	1.54	0.43	0.27	0.42	0.07
新兴前沿11	新型冠状病毒核衣壳蛋白的结构和功能	1.54	0.43	0.27	0.42	0.07

Table 1

Fig.1

Fig.2

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Innovative Practices of Research Governance in Research Institutions Driven by Big Data

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