摘要：

【目的】 通过对国际数据期刊出版质量控制政策的调研与分析,为我国数据期刊的研究与发展提供参考与借鉴。 【方法】 采用网络调查法和内容分析法,对47种国际数据期刊的数据论文提交指南、同行评议方式与标准和作者服务策略三方面的编辑出版政策进行梳理,提炼数据期刊出版质量控制政策的共性要素与特性要素。 【结果】 国际数据期刊的出版质量控制政策着重阐述数据提交规范、数据论文结构(包括传统学术论文继承信息、数据基本信息、数据生产信息、数据重用信息)、同行评议模式、同行评议标准(包括传统学术论文常规审查标准、数据生产方法审查标准、数据审核标准、数据-论文-元数据一致性审核标准),并重视拓展作者服务(提供数据论文写作培训和撰写工具、加强与作者的互动)。 【结论】 数据期刊出版质量控制机制是数据期刊健康发展的重要保障。我国在建设数据期刊时,可参考国际数据期刊已有的良好经验制定出版质量控制政策,使得数据论文编辑出版的各个环节都有章可循、有政策可依。

关键词: 数据期刊, 数据论文, 数据仓储, 数据质量, 质量控制, 同行评议

Abstract:

[Purposes] This paper investigates and analyzes the quality control policies of the international data journals, which is expected to provide references for the development of China's data journal publication. [Methods] A survey on the editorial and publishing policies of 47 international data journals was conducted. The information retrieval and content analysis methods were used to summarize and refine policy elements of the quality control mechanism from the documents of instructions for authors, peer review guidelines, and author services. [Findings] The quality control policies of the international data journals focus on data submission specification, data article structure (including the content inherited from traditional academic papers, basic description of the data, data generation methods, and data reuse instructions), peer review mode, and peer review criteria (including the standards of evaluating the quality of traditional papers, the rigorousness of the data generation methods, the quality of the data, and the consistency among data, manuscript, and metadata). They also attach more importance to author services (such as providing writing training materials, developing writing tools, and interacting with authors). [Conclusions] The quality control mechanism is an important guarantee of the healthy development of the data journals. China's data journals can formulate quality control policies by learning from the good experience of international data journals, so that each step in data paper publication can be instructed by rigorous and reasonable policies.

Key words: Data journal, Data paper, Data repository, Data quality, Quality control, Peer review