摘要：

【目的】 系统梳理数据出版模式及政策发展现状,发现问题并提出建议,为生命科学领域的数据出版实践提供参考。【方法】 将数据出版划分为数据仓储、数据期刊、数据与论文联合出版三种模式,调研各数据仓储、期刊官网及平台,探究不同出版模式的关键要素与特征,以及其对应的数据出版政策,提出生命科学领域数据出版实践中存在的问题及建议。【结果】 数据仓储的出版模式较为普遍,但其建设完备性与质量控制性低、服务方式单一;国内生命科学领域的数据期刊比较缺乏;数据政策涵盖要素较全面,但仍需完善数据出版激励机制、存储标准等要素。【结论】 数据期刊应当注重数据仓储规范,加大数据管理力度;设立本领域数据期刊,提升期刊认可度与影响力;重视学者共享数据的激励机制建设和权益保护,明确数据存储、质量控制等政策,促进融合多形态学术成果的数据出版发展。

关键词: 生命科学, 数据出版, 数据期刊, 数据仓储

Abstract:

[Purposes] This paper reviews the current status of data publishing modes and relevant policies, identifies problems, and makes recommendations for future data publishing in the field of life science.[Methods] We first classified the current practices of data publishing into three modes of data warehousing publishing, data journal publishing, and data-paper co-publishing, and then investigated related data warehousing and official websites and platforms of journals to explore the key elements, characteristics, and policies of each mode. On this basis, we summarized the problems in data publishing practices in life science and proposed suggestions. [Findings] Despite the dominant position in data publishing, data warehousing publishing sees incomplete warehouses, poor quality control, and limited available service modes. There is a lack of data journals in the field of life science in China. An incentive mechanism and a unified data storage standard should be added to the current data publishing policies. [Conclusions] In the future, we should standardize data warehousing, strengthen data management, establish data journals in life science, improve journal recognition and impact, emphasize the incentive mechanism for data sharing and the protection of rights and interests, and detail the policies for data storage and quality control, so as to promote the development of data publishing which displays academic outcomes in multiple forms.

Key words: Life science, Data publishing, Data journal, Data warehousing