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Scientific Data (journal)

Scientific Data is a peer-reviewed, open-access journal published by Springer Nature (Nature Portfolio), launched in 2014 specifically to publish formal, citable descriptions of research datasets. Its primary article type is the Data Descriptor -- not a conventional research article -- which combines a structured, machine-readable description of a dataset (methods, data-collection and processing steps, technical validation, and standardized metadata) with a narrative sufficient for another researcher to understand and reuse the data. A submission qualifies as a Data Descriptor, and is evaluated in peer review, on the technical soundness, completeness, and reusability of the dataset and its documentation -- not on the novelty, scientific impact, or hypothesis-driven conclusions that a traditional research article is judged on. The underlying data must be deposited in a recognized, community-endorsed public repository and made available under an open license; the Data Descriptor itself is the journal article that points to, documents, and formally credits that deposited dataset.

ByCASRAI Editorial Board
· Last updated 23 Jul 2026

Examples

Worked examples

  • Is an instance

    A genomics lab publishes a Data Descriptor in Scientific Data documenting a sequencing dataset's protocol, QC metrics, and repository accession numbers, separate from the research article analyzing the biological findings.

  • Is an instance

    A long-term ecological monitoring dataset with no single novel hypothesis is published as a Data Descriptor because review criteria require technical soundness and documentation, not a hypothesis-driven result.

Counter-examples

Looks similar, but isn't

  • Not an instance

    A manuscript reporting a new experimental finding and drawing a scientific conclusion belongs in a conventional research-article journal, not Scientific Data -- Data Descriptors are reviewed on data quality and documentation, not novelty of a scientific claim.

Editorial commentary

Scientific Data is an open-access journal published by Springer Nature under the Nature Portfolio brand, launched in 2014 (ISSN 2052-4463) to fill a gap traditional research-article journals do not: giving datasets themselves a formal, peer-reviewed, citable publication, independent of whatever paper eventually analyzes them.

Its defining feature is the article type it publishes almost exclusively — the Data Descriptor — rather than the standard IMRaD research article most journals in the Journal Impact Factor tables run.

Data Descriptor: a distinct article type, not a research article

A Data Descriptor pairs a human-readable narrative (background, methods, data-collection and processing workflow, technical validation) with structured, machine-readable metadata describing the dataset itself. The underlying data are deposited in a recognized public repository and released under an open license; the Data Descriptor is the peer-reviewed article that documents, contextualizes, and formally credits that deposited dataset, giving the researchers who generated it explicit, citable authorship credit distinct from whatever downstream analysis papers later reuse the data.

What peer review actually evaluates

This distinction matters for how Data Descriptors are reviewed. Because the article is not presenting a novel finding or hypothesis test, reviewers assess technical rigor and completeness — whether the methods are described in enough detail to reproduce the dataset, whether the technical validation demonstrates the data are fit for reuse, and whether the metadata meet recognized community and metadata standards — rather than judging novelty, significance, or the strength of a scientific conclusion. This is the same broad review philosophy used by other dedicated data journals (for example Elsevier’s Data in Brief and GigaScience Press’s GigaScience), and it is a deliberate departure from how a conventional research-article journal evaluates submissions.

Where it fits relative to a conventional journal

Scientific Data is indexed in Web of Science and receives an annual Journal Citation Reports Journal Impact Factor like any other JCR-indexed title — publicly reported figures have put it in the low-to-high single digits in recent JCR cycles, but the exact current figure should always be checked directly against Clarivate’s Journal Citation Reports rather than cited from a secondary source, since it is recalculated annually. See the general Journal Impact Factor entry for how that metric is computed and why CASRAI treats single-number journal metrics cautiously as a proxy for the quality of any one article. The more important distinction for researchers deciding where to publish a dataset is upstream of any metric: Scientific Data exists to formally publish and credit the dataset itself, not to publish a hypothesis-driven study built on it.

Examples

  • A genomics lab that generates a large sequencing dataset as part of a broader project can publish a Data Descriptor in Scientific Data documenting the sequencing protocol, quality-control metrics, and repository accession numbers, independently of — and often prior to — a separate research article that analyzes the biological findings.
  • A field-survey dataset (e.g., long-term ecological monitoring data) with no single novel hypothesis attached can still be published as a Data Descriptor, since the journal’s review criteria do not require a hypothesis-driven result — only that the data are technically sound, well-documented, and deposited openly.

Counter-example

A manuscript reporting a new experimental finding and drawing a scientific conclusion from that finding belongs in a conventional research-article journal, not Scientific Data — submitting it there as a Data Descriptor would be a category mismatch, since Data Descriptors are reviewed for data quality and documentation completeness, not for the strength or novelty of a scientific claim.

Related terms

  • Journal Impact Factor — the general citation metric Scientific Data, like any JCR-indexed journal, receives annually.
  • Data Management Plan (DMP) — the planning document that often anticipates where and how a dataset will eventually be published or deposited.
  • Open Data — the broader practice of making research data publicly available that Data Descriptors formally document and credit.

Machine-readable encodings

Use in your systems

JATS XML <role> element
xml
<role vocab="credit"
      vocab-identifier="https://casrai.org/dictionary/"
      vocab-term="Scientific Data (journal)"
      vocab-term-identifier="https://casrai.org/dictionary/term/scientific-data" />
Schema.org DefinedTerm (JSON-LD)
json
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  "@type": "DefinedTerm",
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  "sameAs": [],
  "license": "https://creativecommons.org/licenses/by/4.0/",
  "publisher": {
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  },
  "dateModified": "2026-07-23T07:12:21",
  "inLanguage": "en"
}

Referenced across the research world

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