Publishing a research data article in a peer-reviewed data journal linked to a dataset deposited in an appropriate trusted digital repository is a growing trend. The data article implements FAIR (findable, accessible, interoperable, and re-suable) data principles and includes all of the research objects: machine readable and interoperable dataset(s) in a trusted digital repository, associated metadata, computer code (in cases where the raw data have been processed or manipulated), data collection and processing methods, data validation and analyses supporting the quality of the measurements, lineage, provenance, workflows, and usage notes.
The peer review process ensures that these research objects are well documented, quality assured, properly formatted, curated, archived for the long term, and made available immediately upon publication. Critical evaluation through peer review verifies experimental rigor, evaluates the technical quality and completeness of datasets and data descriptors, ensures alignment with Standards, verifies that the data can be easily reused and reanalyzed, and that research based on the data can be reproduced by others in a straightforward manner.
Indexing of published articles accelerates integrative analyses by helping authors and other users find relevant datasets across a wide range of different data-types, and opens doors for new collaborations. A peer-reviewed research data article provides transparency lacking in traditional research articles, increasing credibility and reproducibility, while citation and attribution increases visibility and allow scientists to receive “credit” for this aspect of their research.
Synonyms: Data article
Related terms: Research data, Research article, FAIR