Scientific Data

杂志介绍

Scientific Data杂志介绍

《Scientific Data》是一本以English为主的开放获取国际优秀期刊，中文名称科学数据，本刊主要出版、报道综合性期刊-MULTIDISCIPLINARY SCIENCES领域的研究动态以及在该领域取得的各方面的经验和科研成果，介绍该领域有关本专业的最新进展，探讨行业发展的思路和方法，以促进学术信息交流，提高行业发展。该刊已被国际权威数据库SCIE收录，为该领域相关学科的发展起到了良好的推动作用，也得到了本专业人员的广泛认可。该刊最新影响因子为5.8，最新CiteScore 指数为11.2。

本刊近期中国学者发表的论文主要有：

• A dataset of global ocean alkaline phosphatase activity

  Author: Su, Bei; Song, Xianrui; Duhamel, Solange; Mahaffey, Claire; Davis, Clare; Ivancic, Ingrid; Liu, Jihua

• A comprehensive dataset of annotated brain metastasis MR images with clinical and radiomic data

  Author: Ocana-Tienda, Beatriz; Perez-Beteta, Julian; Villanueva-Garcia, Jose D.; Romero-Rosales, Jose A.; Molina-Garcia, David; Suter, Yannick; Asenjo, Beatriz; Albillo, David; Ortiz de Mendivil, Ana; Perez-Romasanta, Luis A.; Gonzalez-Del Portillo, Elisabet; Llorente, Manuel; Carballo, Natalia; Nagib-Raya, Fatima; Vidal-Denis, Maria; Luque, Belen; Reyes, Mauricio; Arana, Estanislao; Perez-Garcia, Victor M.

• A new kinematic dataset of lower limbs action for balance testing

  Author: Dong, Anqi; Wang, Fei; Shuai, ZhenYu; Zhang, Kaiyu; Qian, Dexing; Tian, Yinsheng

• The chromosome-level genome of Cherax quadricarinatus

  Author: Chen, Honglin; Zhang, Rui; Liu, Feng; Shao, Changwei; Liu, Fangfang; Li, Weidong; Ren, Jindong; Niu, Baolong; Liu, Haipeng; Lou, Bao

英文介绍

Scientific Data杂志英文介绍

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.