Scientific data management policy in China: a quantitative content analysis based on policy text

Abstract

Purpose

This paper aims to understand the current development situation of scientific data management policy in China, analyze the content structure of the policy and provide a theoretical basis for the improvement and optimization of the policy system.

Design/methodology/approach

China's scientific data management policies were obtained through various channels such as searching government websites and policy and legal database, and 209 policies were finally identified as the sample for analysis after being screened and integrated. A three-dimensional framework was constructed based on the perspective of policy tools, combining stakeholder and lifecycle theories. And the content of policy texts was coded and quantitatively analyzed according to this framework.

Findings

China's scientific data management policies can be divided into four stages according to the time sequence: infancy, preliminary exploration, comprehensive promotion and key implementation. The policies use a combination of three types of policy tools: supply-side, environmental-side and demand-side, involving multiple stakeholders and covering all stages of the lifecycle. But policy tools and their application to stakeholders and lifecycle stages are imbalanced. The development of future scientific data management policy should strengthen the balance of policy tools, promote the participation of multiple subjects and focus on the supervision of the whole lifecycle.

Originality/value

This paper constructs a three-dimensional analytical framework and uses content analysis to quantitatively analyze scientific data management policy texts, extending the research perspective and research content in the field of scientific data management. The study identifies policy focuses and proposes several strategies that will help optimize the scientific data management policy.

Citation

Si, L., Liu, L. and He, Y. (2024), "Scientific data management policy in China: a quantitative content analysis based on policy text", Aslib Journal of Information Management, Vol. 76 No. 2, pp. 269-292. https://doi.org/10.1108/AJIM-05-2022-0257