Scientific Data SCIESCI

Scientific Data is a peer-reviewed, open-access journal for descriptions of scientifically valuable datasets, and research that advances the sharing and reuse of scientific data. We aim to promote wider data sharing and reuse, and to credit those that share.

Scientific Data primarily publishes Data Descriptors, a new type of publication that provides detailed descriptions of research datasets, including the methods used to collect the data and technical analyses supporting the quality of the measurements. Data Descriptors focus on helping others reuse data, rather than testing hypotheses, or presenting new interpretations, methods or in-depth analyses.

Scientific Data also welcomes submissions describing analyses or meta-analyses of existing data, and original articles on systems, technologies and techniques that advance data sharing and reuse to support reproducible research.

Scientific Data offers a streamlined but thorough peer-review process that evaluates the rigour and quality of the experiments used to generate the data and the completeness of the description of the data. The actual data are stored in one or more public, community-recognized repositories, and release of the data is verified as a condition of publication.

Scientific Data is open to submissions from a broad range of natural science disciplines, including, but not limited to, data from the life, biomedical and environmental science communities. Submissions may describe big or small data, from new experiments or value-added aggregations of existing data, from major consortiums and single labs. We are also willing to consider descriptions of quantitative datasets from the social sciences, particularly those that may be of use for integrative analyses that stretch across the traditional discipline boundaries between the life, biomedical, environmental and social sciences.

Scientific Data 是一本经过同行评审的开放获取期刊，用于描述具有科学价值的数据集，以及促进科学数据共享和重用的研究。我们的目标是促进更广泛的数据共享和重用，并对共享者表示敬意。

Scientific Data 主要数据描述符，这是一种新型出版物，提供研究数据集的详细描述，包括用于收集数据的方法和支持测量质量的技术分析。数据描述符专注于帮助他人重复使用数据，而不是测试假设，或提出新的解释、方法或深入分析。

Scientific Data 还欢迎提交描述对现有数据进行分析或元分析的文章，以及有关促进数据共享和重用以支持可重复研究的系统、技术和技巧的原创文章。

Scientific Data 提供了一个精简但全面的​​同行评审流程，用于评估用于生成数据的实验的严谨性和质量以及数据描述的完整性。实际数据存储在一个或多个社区认可的公共存储库中，并且数据的作为条件进行验证。

科学数据对来自广泛自然科学学科的提交开放，包括但不限于来自生命、生物医学和环境科学界的数据。提交的内容可以描述大数据或小数据，来自新实验或现有数据的增值聚合，来自主要联盟和单个实验室。我们还愿意考虑对来自社会科学的定量数据集的描述，尤其是那些可能用于跨越生命、生物医学、环境和社会科学之间传统学科界限的综合分析的那些。

该刊已被国际权威数据库SCIE、SCI收录，是国际顶级期刊。该刊致力于发表经过严格同行评审的高质量原创文章，反映Social Sciences-Education领域的新进展、新技术、新成果，促进该领域科研交流和科研成果转化。该刊2022年影响因子为9.8，平均审稿速度为16 Weeks，近三年来没有被列入预警名单。如果您需要投稿发表服务及指导，可以联系我们的客服老师，我们专业专注服务期刊投稿协助10年，为您提供期刊投稿个性化定制服务，并且我们确保严格保密您的个人信息及稿件内容。