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期刊名
Scientific Data
SCI DATA
ISSN / eISSN
2052-4463 / 2052-4463
目标和范围
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 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.
研究方向
综合性期刊
CiteScore
11.20
查看趋势图
CiteScore 学科排名
| 类别 | 分区 | 排名 |
|---|---|---|
| Mathematics - Statistics and Probability | Q1 | #3/262 |
| Mathematics - Education | Q1 | #20/1469 |
| Mathematics - Statistics, Probability and Uncertainty | Q1 | #3/160 |
| Mathematics - Library and Information Sciences | Q1 | #6/266 |
| Mathematics - Computer Science Applications | Q1 | #55/792 |
| Mathematics - Information Systems | Q1 | #32/379 |
Web of Science 核心合集
| Science Citation Index Expanded (SCIE) | Social Sciences Citation Index (SSCI) |
|---|---|
| Indexed | - |
| 类别 (Journal Citation Reports 2023) | 分区 |
|---|---|
| MULTIDISCIPLINARY SCIENCES - SCIE | Q1 |
H-index
35
出版国家或地区
ENGLAND
出版商
Springer Nature
出版年份
2014
年文章数
761
Open Access
YES
通讯方式
HEIDELBERGER PLATZ 3, BERLIN, GERMANY, 14197
认证评论
Annual Publication Volume: Around 400 articles per year, averaging 1 article per day.
Review Speed: The review process is fast, with prompt feedback. Results are given within 3 months.
Submission Results: From submission to acceptance, there was one major revision in between and it has been accepted.
Experience Sharing: This journal places great emphasis on the rigor of data and the importance of data validation. The submission process involves stages such as assistant editor, editor, two reviewers, revision, re-review (with a different reviewer), editorial board, and chief editor, lasting for 1 year. In addition to data analysis, dataset creation, and writing, it takes a total of 2 years to complete. Therefore, one must be mentally prepared for long-term submissions.
On June 28th, each author receives an email;
On June 30th, the QC results are returned, and because the article lacks "code availability," it is supplemented and resubmitted on the same day. The status shows "Initial QC Complete";
On July 2nd, the status changes to "Editor Assignment";
On July 5th, QC returns again, and the editor refuses to accept the SRA reviewer link, requesting the data to be made public and the link to be modified. After making the changes, it is resubmitted, and the status shows "Editor Assignment".
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