情报科学 ›› 2024, Vol. 42 ›› Issue (6): 21-28.

• 理论研究 • 上一篇    下一篇

基于政策特征的我国科学数据汇交一致性评价分析

  

  • 出版日期:2023-06-01 发布日期:2024-07-31

  • Online:2023-06-01 Published:2024-07-31

摘要: 【 目的/意义】分析评价科学数据汇交政策,有助于规范我国科学数据汇交流程、提高汇交工作效率,推动科 研活动全流程诚信管理。【方法∕过程】融合政策目标、政策工具、政策领域三个维度,评价我国科学数据汇交政策在 政策目标上的协同程度、政策工具的组配情况与政策领域间的协作情况,以及政策内部各要素之间的一致性程度。 【结果/结论】我国科学数据汇交政策体系基本实现了多政策目标协同和多政策领域协调,且政策内部一致性水平 良好,但存在对数据归档重视程度不足、过度依赖环境型政策工具等问题,应从规范数据归档流程与创新数据服务 模式等方面助推科研诚信建设和完善数据增值机制。【创新/局限】探索了融合政策多维特征的科学数据汇交政策 内外部一致性评价策略,应进一步挖掘政策内容特征、评价变量及其关系。

Abstract: 【 Purpose/significance】 Analyzing and evaluating scientific data archiving policies can help standardize the process of sci⁃ entific data archiving in China, improve the efficiency of archiving, and thus promote the integrity management of the whole process of scientific research activities.【 Method/process】 This paper evaluates the degree of synergy among the policy objectives, the grouping of policy tools and the collaboration among policy areas in China′s scientific data archiving policies from three dimensions: policy ob⁃ jectives, policy tools and policy areas; and calculates the degree of consistency among the elements within the assessed policies.【 Re⁃ sult/conclusion】 The analysis finds that China′s scientific data archiving policy system basically achieves the synergy of multiple policy objectives and coordination of multiple policy areas, and the level of internal consistency of the policy is commendable, but there are problems such as insufficient attention to data archiving and over-reliance on environment-based policy tools. To help pro⁃ mote the construction of scientific research integrity and improve the data value-added mechanism, the data archiving process should be standardized to help, and the data service model should be innovated.【 Innovation/limitation】 A consistency evaluation strategy of scientific data archiving policy, including internal and external aspects, was explored that integrates the multi-dimensional character⁃ istics of policy. The evaluation system should further explore policy content characteristics, evaluation variables and their relationship.