China Scientific Data
Jointly sponsored by the Computer Network Information Center, Chinese Academy of Sciences, and the Chinese National Committee for CODATA, advised by National Science & Technology Infrastructure Center, China Scientific Data (CN11-6035/N,ISSN 2096-2223) is a bilingual open-access quarterly publishing data papers of multidisciplinary fields in English and Chinese. It is indexed by Chinese Science Citation Database (2019-2020).
The journal is dedicated to promoting the sharing and citation of scientific data, and to making them findable, accessible, intelligible and reusable..
Data papers describing (but not limited to) the following:
(1)Datasets or data products generated from major scientific activities;
(2)Derived datasets or data products refined from raw data;
(3)Datasets linked to existing publications
China Scientific Data does NOT publish new research findings, or techniques, methods and cases concerning data quality researches and data applications.
Why Publish in China Scientific Data
Articles together with datesets published by China Scientific Data shall be reused under the Creative Commons Attribution 4.0 International License (CC BY 4.0). Users have the right to read, download, copy, distribute, print, search, or link to the full texts of these articles and datesets.
Professional publishing for data papers and data sets
Strict observance shall cover both articles and datasets to guarantee the quality of the publication as well as the reuse of the datasets.
Efficient processing, high exposure,rapid dissemination and intelligent services
All the publishing process shall be carried out through this platform online transparently. Datasets are recommended to make storage and supply open services in an accredited data repository(e.g., www.sciencedb.cn). Data papers and datasets are linked by DOI and semantic web has been developing to provide further information about the usage of data.
Online phased peer review, driving high transparency
Both peer review and crowd rating are employed to make the datasets and their data papers more accessible, intelligible and reusable.