科学数据价值增值影响因素系统动力学仿真研究

doi:10.13998/j.cnki.issn1002-1248.23-0699

摘要/Abstract

摘要： [目的/意义]探究科学数据价值增值影响因素,揭示科学数据价值增值内在发展规律。[方法/过程]基于专家访谈资料和文献中科学数据价值增值相关内容,采用扎根理论方法,得到科学数据价值增值影响因素的理论模型。在此基础上,建立科学数据价值增值系统动力学模型,对科学数据价值增值的过程进行动态模拟仿真与分析,揭示各影响因素对科学数据价值增值的作用关系。[结果/结论]科学数据价值增值过程中,原始数据质量是前提条件,数据存缴水平影响显著,数据组织与整合是价值增值形成的关键,科学数据共享与开发是价值增值实现的关键。

关键词: 科学数据, 价值增值, 影响因素, 动力学仿真, 数据要素, FAIR

Abstract: [Purpose/Significance] To explore the influencing factors of the added value of scientific data and reveal the inherent development laws of the added value of scientific data. [Method/Process] First, based on the interview data of 18 experts and the research results related to the value appreciation of scientific data in existing literature, the grounded theory method was adopted. Through open coding, main-axis coding, and selective coding, 19 categories, 6 main categories, and 3 core categories were finally obtained. From this, a theoretical model of the factors influencing the value appreciation of scientific data was obtained. On this basis, the Vensim PLE tool was used to establish a dynamic model of the value appreciation system of scientific data, and the process of value appreciation of scientific data was dynamically simulated and analyzed to reveal the relationship between various influencing factors and the value appreciation of scientific data. [Results/Conclusions] In the process of increasing the value of scientific data, the quality factor of raw data is a prerequisite, and high-quality raw scientific data are conducive to the integration and secondary development of subsequent scientific data. The data literacy of data producers represented by researchers has the most significant impact on the quality of scientific data. The level of data storage and payment has a significant impact on the added value of scientific data. When the perceived effort and perceived risk of data storage and payment by researchers decrease, accompanied by the pressure of scientific data sharing policies, researchers become more likely to increase their willingness to save and pay, thereby significantly improving the scale effect of data storage and payment. The organization and integration of scientific data is the key to the formation of value-added scientific data. Overall, the metadata quality has the most significant impact on the level of scientific data organization and integration. The quality of metadata is the foundation of scientific data processing, classification, and integration. The higher the quality of metadata, the more it helps to improve the level of scientific data organization and integration. The sharing and development of scientific data is the key to realizing the value-added of scientific data. It is the final step in realizing the value-added of scientific data. In this process, the scale of scientific data openness, the quality of scientific data sharing platforms, and development capabilities all have a positive promoting effect on the level of scientific data sharing and development.

Key words: scientific data, value increment, influencing factors, system dynamics, data elements, FAIR

中图分类号:

G203

孙俐丽, 王伟杰, 盛杰霏. 科学数据价值增值影响因素系统动力学仿真研究[J]. 农业图书情报学报, 2023, 35(9): 28-42.

SUN Lili, WANG WeiJie, SHENG Jiefei. Influencing Factors of Scientific Data Value Increment Based on System Dynamics[J]. Journal of Library and Information Science in Agriculture, 2023, 35(9): 28-42.

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