Scientific Data

SJR Rank #1,582H-index: 165SJR: 1.907Best quartile: Q1Open AccessAPC: US$2,490Listed in DOAJ
Journal website: aims, scope and author guidelines
Publisher

Nature Research

Country

United Kingdom

Type

journal

SJR by Edition

2022202500.651.31.952.6

Subject Categories

  • Computer Science ApplicationsQ1
  • EducationQ1
  • Information SystemsQ1
  • Library and Information SciencesQ1
  • Statistics and ProbabilityQ1
  • Statistics, Probability and UncertaintyQ1

Areas: Computer Science · Decision Sciences · Mathematics · Social Sciences

Most published research topics

Genomics and Phylogenetic StudiesChromosomal and Genetic VariationsRemote Sensing in AgricultureClimate variability and modelsEEG and Brain-Computer InterfacesSpecies Distribution and Climate ChangeFunctional Brain Connectivity StudiesMachine Learning in Materials ScienceHydrology and Watershed Management StudiesLand Use and Ecosystem Services

Source: OpenAlex

Publication Statistics

2025 Docs3-Year DocsCitable Docs0800160024003200

Documents per Year

202220250550110016502200

Detailed Information

ISSN

2052-4463

SJR Best Quartile

Q1

Region

Western Europe

Citations per Document (2 years)

6.78

References per Document

49.78

Coverage

2014-2026

Scope

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.

Metrics from SCImago Journal Rank 2025. View on SCImago