Abstract:

[Purposes] This study aims to explore a quantitative evaluation framework for the impact of data papers in the context of new scientific data publication patterns, implement an evaluation practice for the impact of data papers in China, and provide recommendations for the development of data paper publication and scientific data sharing and reuse. [Methods] Starting from a dual perspective of “scientific data attributes” and “academic paper attributes”, this study conceptualizes various attributes of data papers and visualizes their impact through six evaluation variables: format standardization, breadth of academic impact, depth of academic impact, social impact, scientific content, and data dissemination effectiveness. These variables are quantified into a series of specific measurement indicators, culminating in a comprehensive impact composite indicator designed based on a multidimensional quantitative indicator system. Using the Chinese science citation database (CSCD) and Elsevier’s Scopus database as data sources, this paper quantitatively evaluates the impact of data papers published by Chinese researchers based on the proposed evaluation methodology. [Findings] The findings reveal that current standards for defining data papers are not yet unified, the publication formats of data papers need to be standardized, and there is an imbalance in the publication of data papers in international and domestic data journals. There are significant differences in the volume of data papers published across various disciplines, with varying levels of emphasis on scientific data. [Conclusions] It is essential to enhance the promotion and application of standards related to the publication of data papers and to increase the support of science and technology policies for data paper publishing. This can be achieved by encouraging journals to create dedicated Data Paper Sections, collaborating with scientific data repositories, and establishing best practices for open data. Furthermore, the development of methods to evaluate and promote the expansion and improvement of data journals should be further pursued.

Key words: Scientific data paper, Impact, Quantitative evaluation, Publication standards

摘要：

【目的】面向新型科学数据出版模式,探索数据论文影响力定量评价体系,并对中国数据论文影响力评价进行实践,为数据论文出版及科学数据共享重用提供发展建议。【方法】从数据论文的“科学数据属性”和“学术论文属性”双重视角出发,对论文的各类属性进行概念化转换,将其影响力具像化为格式规范度、学术影响力广度、学术影响力深度、社会影响力、内容科学性和数据传播效力6个评价变量,并量化为一系列具体测度指标,基于多维度量化指标体系设计综合性影响力复合指标。以中国科学引文数据库和爱斯唯尔Scopus数据库为数据来源,基于本文提出的数据论文影响力评价方法,对我国科研人员发表的数据论文进行影响力定量评价。【结果】评价结果表明,当前数据论文的概念界定标准仍未统一,数据论文的出版形式有待规范,我国在国际和国内期刊上发表数据论文存在不均衡现象,各学科领域发表的数据论文体量差异较大,对科学数据的重视程度各有侧重。【结论】应增强数据论文出版相关标准的推广和应用,加大数据论文出版的科技政策支持力度,通过鼓励期刊增设《数据论文栏目》、与科学数据存储库合作等形式建设开放数据最佳实践,并进一步发展以评价促进数据期刊扩容提质的方法路径。

关键词: 科学数据论文, 影响力, 定量评价体系, 出版规范