雜志介紹

Scientific Data雜志介紹

《Scientific Data》是一本以English為主的開放獲取國際優秀期刊，中文名稱科學數據，本刊主要出版、報道綜合性期刊-MULTIDISCIPLINARY SCIENCES領域的研究動態以及在該領域取得的各方面的經驗和科研成果，介紹該領域有關本專業的最新進展，探討行業發展的思路和方法，以促進學術信息交流，提高行業發展。該刊已被國際權威數據庫SCIE收錄，為該領域相關學科的發展起到了良好的推動作用，也得到了本專業人員的廣泛認可。該刊最新影響因子為5.8，最新CiteScore 指數為11.2。

本刊近期中國學者發表的論文主要有：

• 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

英文介紹

Scientific Data雜志英文介紹

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.