Examples
Worked examples
- Is an instance
A Scientific Data paper describing a 10-year ocean-current monitoring dataset
Counter-examples
Looks similar, but isn't
- Not an instance
A research article that uses a dataset to answer a question is not a data paper (the dataset is means, not subject)
Editorial commentary
A data paper (also called a data descriptor) is a peer-reviewed publication that describes a dataset — its collection methods, structure, processing, and quality — rather than presenting novel scientific analysis or findings derived from that data. Data papers were established to give citable scholarly credit for the substantial work of producing a well-documented, reusable dataset, work that traditional research articles rarely recognise on its own terms.
How review differs from a research article
Data-paper review focuses on data quality, completeness, and documentation — whether the dataset is well-described, technically sound, and usable by others — rather than on the novelty or significance of a scientific claim, since a data paper is not making one. Exemplar venues include Scientific Data (Nature Portfolio), Earth System Science Data (Copernicus), and Data in Brief (Elsevier), each of which structures review around methodological and technical-validation criteria specific to describing a dataset rather than testing a hypothesis.
What it is not
A data paper is not the same as simply depositing a dataset in a repository without an accompanying descriptor article: deposit alone typically gets a dataset a persistent identifier and basic repository metadata, while a data paper adds a peer-reviewed narrative — a technical-validation section, methodological detail, and usage notes — that a bare repository record does not require. A data paper is also not a vehicle for reporting new scientific findings; a paper that draws substantive conclusions from the data it describes is a conventional research article, not a data paper, even if it also documents a dataset.
In practice
Data papers are closely tied to the FAIR Principles (Findable, Accessible, Interoperable, Reusable) for scientific data management, since a well-written data paper is one practical mechanism for making a dataset genuinely findable and reusable by others, and to broader data availability and open data practices — a data paper can serve as the detailed, citable companion to a briefer data availability statement in a separate research article.
References
- Wilkinson et al. 2016 Scientific Data (FAIR Principles)
- Chavan and Penev 2011 ‘The data paper: a mechanism to incentivize data publishing’ BMC Bioinformatics
Also known as
Data descriptor · Dataset paper
Machine-readable encodings
Use in your systems
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