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Sci Data. 2023 Sep 26;10(1):656. doi: 10.1038/s41597-023-02491-7.
Software and data citation are emerging best practices in scholarly communication. This article provides structured guidance to the academic publishing community on how to implement software and data citation in publishing workflows. These best practices support the verifiability and reproducibility of academic and scientific results, sharing and reuse of valuable data and software tools, and attribution to the creators of the software and data. While data citation is increasingly well-established, software citation is rapidly maturing. Software is now recognized as a key research result and resource, requiring the same level of transparency, accessibility, and disclosure as data. Software and data that support academic or scientific results should be preserved and shared in scientific repositories that support these digital object types for discovery, transparency, and use by other researchers. These goals can be supported by citing these products in the Reference Section of articles and effectively associating them to the software and data preserved in scientific repositories. Publishers need to markup these references in a specific way to enable downstream processes.
软件和数据引用是学术交流中新兴的最佳实践。本文为学术出版界提供了结构化的指导，介绍如何在出版工作流程中实施软件和数据引用。这些最佳实践支持学术和科学成果的可验证性和可重复性、有价值数据和软件工具的共享和重用，以及对软件和数据创建者的归因。虽然数据引用越来越完善，但软件引用正在迅速成熟。软件现在被认为是一个关键的研究成果和资源，需要与数据一样具有透明度、可访问性和披露程度。支持学术或科学成果的软件和数据应保存在支持这些数字对象类型的科学知识库中，以实现发现、透明度，并供其他研究人员使用。这些目标可以通过在文章的参考文献部分引用这些产品，并有效地将其与保存在科学知识库中的软件和数据相关联来实现。出版商需要以特定的方式标记这些参考文献，以支持下游流程。
