Good Data Governance Practice and a Grading Initiative for Life Sciences Data
Chinese Medical Sciences JournalPages: 1-8(2026)
Updated:2026-03-30
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Good Data Governance Practice and a Grading Initiative for Life Sciences Data
“Life sciences have entered the era of big data, uncovering the complexity of human biological systems and advancing precision medicine and scientific wellness. Here, we introduce a novel framework for Good Data Governance Practice (GDGP) coupled with a grading initiative for the life sciences, focusing on traceability and openness. The GDGP framework systematically defines governance constraints, influencing factors, and functional capabilities to streamline data governance and management efficiency. This achievement lays the groundwork for compliant cross-institutional and cross-border data sharing and collaborative processing, poised to pave the way for standardized, ethical, and scalable data-driven research in precision medicine and beyond.”
Affiliations:
1.Human Phenome Institute, Fudan University, Shanghai 201203, China
2.International Human Phenome Institutes (Shanghai), Shanghai 200433, China
3.National Population Health Data Center, Chinese Academy of Medical Sciences, Beijing 100020, China
4.Shanghai GENE Institute for Clinical Translation, Shanghai 201203, China
5.China National Center for Bioinformation, Beijing 100101, China
6.China National Health Development Research Center, Beijing 100044, China
7.Intelligent Medicine Institute, Fudan University, Shanghai 200032, China
Liu Han,Li Jing,Zhang Sheng-Fa,et al.Good Data Governance Practice and a Grading Initiative for Life Sciences Data[J].Chinese Medical Sciences Journal,
Liu Han,Li Jing,Zhang Sheng-Fa,et al.Good Data Governance Practice and a Grading Initiative for Life Sciences Data[J].Chinese Medical Sciences Journal,DOI:.
Good Data Governance Practice and a Grading Initiative for Life Sciences Data