CAS' new English data journal to aid research

中国科学院为新推出的英文数据期刊研究提供帮助

China launched its first English-language data journal in Beijing on Tuesday, underscoring the growing strategic importance of scientific data in artificial intelligence-driven research worldwide.

周二在我国北京推出了第一份英文数据期刊，其中强调了科学数据在全球人工智能驱动的研究中日益增长的战略重要性。

Titled Data Express, the open-access journal is sponsored by the Chinese Academy of Sciences and edited by Yu Guirui, an ecologist and member of the CAS. It serves as the flagship of a cluster of 20 titles — one comprehensive journal and 19 discipline-specific publications — covering strategic fields including AI corpus research, ecosystem science, ocean science, lightning data, biomedicine, materials science and agriculture.

这份名为《数据快报（英文）》的开放获取期刊由中国科学院主办，由生态学家、中国科学院院士于贵瑞编辑。它是20种期刊的旗舰刊——一种综合性期刊和19种学科特定出版物——涵盖人工智能语料库研究、生态系统科学、海洋科学、闪电数据、生物医学、材料科学和农业等战略领域。

Sun Degang, Party secretary of the CAS Computer Network Information Center, said scientific data has become a strategic national resource in the era of big data and AI.

中科院计算机网络信息中心党委书记孙德刚表示，在大数据和人工智能时代，科学数据已成为国家战略资源。

"Data journals serve as a crucial lever to encourage open data sharing, improve data governance, and empower new research paradigms," Sun said.

“数据期刊是鼓励科学数据开放共享、完善科学数据治理体系的重要抓手，”孙德刚说。

Yu noted that making high-value scientific data findable, accessible, interoperable and reusable — known as the FAIR principles — is a shared global challenge.

于贵瑞指出，让高价值的科学数据可发现、可访问、可互操作和可重用——这也就是被称为FAIR原则，是一个共同的全球挑战。

"Data Express is our response to that challenge. It not only fills a gap in China's high-end data publishing sector, but also offers a Chinese hub for global scientific data exchange, enabling barrier-free circulation and collaboration," Yu said.

“《数据快报（英文）》是我们对这一挑战的回应。它不仅填补了中国高端数据出版领域的空白，也为全球科学数据交换提供了一个中国枢纽，实现了无障碍的流通和协作，”于贵瑞说。

Zhang Yun, deputy director of the CAS Bureau of Basic Capacity for Science and Technology, said data journals enable long-confined, high-quality scientific data — much of it generated by engineers and technicians at large-scale facilities and field stations — to be made accessible, giving due credit to contributors. Such data provides critical fuel for "AI for Science" and supports global research progress.

中国科学院科技基础能力局副局长张韵表示，数据期刊使长期受限的高质量科学数据——其中大部分是由大型设施和试验站的工程师和技术人员生成的——变得可访问，这归因于它的贡献者。此类数据为“AI for Science”提供了关键燃料，并帮助全球研究进展。

"Data papers are recognized as formal academic outputs," Zhang said, adding that the CAS is drafting guiding measures to encourage institutes to include such contributions in professional promotion and degree-awarding evaluations.

“数据论文被认为是正式的学术成果，”张韵说，并表示中国科学院正在起草指导措施，鼓励研究所将此类贡献纳入专业晋升和学位授予评估之中。

The cluster's design is anchored in China's national science data center system. The 19 discipline-specific journals correspond to established sub-centers across various fields, ensuring a steady pipeline of high-quality data submissions from the outset, Zhang added.

该期刊集群的设计基于中国国家科学数据中心系统建造。张韵补充说，19种学科特定期刊相当于各个领域已建立的分中心，确保从一开始就有稳定的高质量数据提交渠道。

Zhang expressed confidence in the cluster's international competitiveness, noting that Chinese scholars already account for nearly 40 percent of the world's high-quality scientific papers.

张韵对该期刊集群的国际竞争力充满信心，他指出中国学者发表的论文已经占世界高质量科学论文的近40%。

Zhang Fan, deputy general manager of China Science Publishing &Media, whose SciEngine platform supports the cluster, said the initiative also addresses a long-standing vulnerability in China's academic publishing ecosystem — the "both ends outside" dilemma, where Chinese scientists publish their papers and store data on foreign platforms.

中国科学出版传媒副总经理张凡表示，依托SciEngine来支持该期刊集群，还解决了中国学术出版生态系统中一个长期存在的漏洞——“两头在外”的困境，即中国科学家在国外平台上发表论文和存储数据。

"Scientific data is a strategic resource, especially in the AI era. The data we feed into AI models may be even more valuable than individual papers. Keeping that data on a platform easily accessible for scientists is essential," Zhang Fan said.

“科学数据是一种战略资源，尤其是在人工智能时代。我们输入人工智能模型的数据可能比单个论文更有价值。将这些数据保存在科学家易于访问的平台上对我们来说至关重要，”张凡说。

The SciEngine platform is fully self-developed and domestically produced, and currently serves more than 1,000 journals. It connects directly with nearly 20 international databases, including Web of Science and Scopus, ensuring global visibility while retaining data sovereignty, he added.

SciEngine全面自研国产化，目前服务期刊超过1000种。他补充说，它直接连接到近20个国际数据库，包括Web of Science和Scopus，确保成果可全球检索，同时保有数据主权。

"Unlike conventional articles that typically publish only positive findings, data journals also welcome well-documented negative or null results," Zhang Fan said, noting that these are particularly valuable in fields such as materials science for helping researchers avoid duplicating effort and for providing high-quality training corpora for AI models.

张凡说：“与通常只发表积极发现的传统文章不同，数据期刊也欢迎有据可查的阴性结果或零结果。”他指出，这些在材料科学等领域尤其有价值，可以帮助研究人员避免重复工作，并为人工智能模型提供高质量的训练语料库。

"Globally, data journals are a relatively recent development, with leading titles such as Elsevier's Data in Brief and Springer's Scientific Data emerging only around 2014," he said. "China's first Chinese-language data journal, China Scientific Data, was launched in 2016 — almost in step with global progress."

“在全球范围内，数据期刊有一个相对较新的发展，像Elsevier的Data in Brief和Springer的Scientific Data这样的顶级期刊直到2014年左右才出现，”他说。“中国第一本中文数据期刊《中国科学数据》于2016年创刊——几乎与全球进步同步。”

"Data journals are an integral part of the national strategy to build world-class scientific journals. This clustered launch places China in a strong position to run neck and neck with, or even surpass, international leaders in this emerging field," Zhang Fan said.

“数据期刊是建设世界一流科学期刊国家战略必要的组成部分，此次的聚合推出使中国在这一新兴领域处于与国际领先者并驾齐驱甚至超越的强势地位，”张凡说。