Data Availability Statement Examples by Journal

A data availability statement (DAS) is a required manuscript section that tells readers exactly where to find the data behind a paper’s results — the repository, a persistent identifier such as a DOI, and any access conditions. ICMJE, PLOS, Springer Nature, and NIH each mandate specific wording; a vague statement without a locatable, retrievable dataset fails reproducibility review.

What a data availability statement must include

At minimum, a usable DAS answers four questions: where the data is, how to get it, what (if anything) restricts access, and who to contact if access is conditional. Concretely:

Location and persistent identifier. Name the specific repository and give a DOI or accession number, not just a homepage URL. Springer Nature’s own guidance offers a representative template: “The datasets generated during and/or analysed during the current study are available in the [NAME] repository, [PERSISTENT WEB LINK TO DATASETS].” A CASRAI repository is expected to curate material well enough to support discovery and reuse, which is exactly what a stable identifier is for.
Access conditions. If data is openly available, say so plainly. If it isn’t, PLOS’s data-availability policy is explicit that “available from the corresponding author upon request” is not sufficient on its own — a restriction has to be backed by a documented legal or ethical constraint, and the named contact should be an institutional body (an ethics committee or data access committee), not an individual researcher.
For clinical trials specifically, more is required. Under the International Committee of Medical Journal Editors’ (ICMJE) 2017 policy, manuscripts reporting clinical trial results submitted to ICMJE-following journals after 1 July 2018 must include a data sharing statement that states whether individual participant data will be shared, what data specifically, whether related documents (protocol, statistical analysis plan) will be available, and by what access criteria and mechanism. Trials that began enrolling on or after 1 January 2019 must also register a data-sharing plan on the trial’s public registration.
A rationale that maps to FAIR, not just to the journal’s checklist. The FAIR principles (Findable, Accessible, Interoperable, Reusable — Wilkinson et al., Scientific Data, 2016) are the underlying standard most of these journal and funder policies are informally reaching for. A DAS that names a real repository and a persistent identifier is doing the “Findable” and “Accessible” work directly; it says nothing about “Interoperable” or “Reusable” unless the deposited data also carries proper metadata and documented formats.

Writing one that actually supports reproducibility

A DAS can satisfy a journal’s submission system and still fail to help anyone reproduce the work. The gap is usually one of these:

Deposit before you cite. Get the accession number or DOI before writing the statement, not a placeholder to fill in later. A statement that says “will be made available upon publication” without a working identifier is a promise, not a pointer.
Name the exact repository, not a category of repository. “Deposited in a public repository” tells a reader nothing they can act on; “deposited in Zenodo, DOI 10.5281/zenodo.XXXXXXX” does.
Address code alongside data if the analysis needs it. The Center for Open Science’s Transparency and Openness Promotion (TOP) Guidelines frame this as a tiered standard: Level 1 requires disclosing whether data are available, Level 2 requires the data actually be available (or the constraint explained), and Level 3 requires that the publicly available data can be used to computationally reproduce the results. A DAS aimed at genuine reproducibility should be written to Level 3’s bar even where a journal only enforces Level 1 — which means naming where analysis code lives too, not just the raw data.
State restrictions precisely, and name an institutional contact. “Restricted due to participant privacy; requests may be made to the [Institution] Data Access Committee, [contact/URL]” is checkable. “Available on request” is not, on its own.
Keep the statement in sync with the deposit. If an accession number changes between a private peer-review link and the public record, update the published statement — a DAS that points to a dead or superseded link fails the reader even though it was accurate at submission.

Do all journals require one? What publishers and funders actually mandate

No single universal mandate covers every journal, but requirements are broad and expanding, and they differ by publisher, discipline, and funder:

PLOS has required a DAS across its journals since its 2014 open-data policy, with data expected in a public repository “with rare exception,” and refusal to comply is explicit grounds for rejection.
ICMJE-following journals require a data sharing statement specifically for clinical trial manuscripts, as described above — this is narrower than “every ICMJE journal, every article type.”
Springer Nature / Nature Portfolio requires data availability statements as part of its reporting standards across its journals, with several standard template forms depending on where the data actually lives (repository, supplementary files, restricted access).
TOP Guidelines signatories — over 5,000 organizations and more than 1,100 journals have adopted at least one TOP standard, most commonly data citation and availability requirements, per the Center for Open Science.
Funders add a related but distinct requirement. NIH’s Data Management and Sharing Policy, effective 25 January 2023, requires a data management and sharing plan for essentially all NIH-funded research that generates scientific data. That plan is submitted with the grant application, not the paper — it is the funder-side counterpart to a data management plan, and it’s worth not conflating the two: a DMP is a forward-looking plan filed with a funder before the work happens, while a DAS is a retrospective statement filed with a journal once results exist. Complying with one doesn’t automatically satisfy the other, though a well-executed DMP makes writing an accurate DAS later considerably easier.

Net effect: if a manuscript is going to a journal that has adopted PLOS-style, TOP-aligned, or ICMJE-style policies — which now covers most major biomedical and multidisciplinary publishers — a DAS is effectively mandatory. Outside those, it’s increasingly expected as good practice even where not strictly enforced.

Example wording for common situations

Data in a public repository: “The datasets generated and analysed during the current study are available in the Zenodo repository, https://doi.org/10.5281/zenodo.XXXXXXX.”
Controlled/restricted access: “Data are available under controlled access via dbGaP study accession phsXXXXXX, subject to approval by the [Institution] Data Access Committee.”
Embargoed data: “Data underlying this study are subject to a 12-month embargo and will be deposited in [repository] and made publicly available no later than [date].”
Data included in the article: “All data generated or analysed during this study are included in this published article and its supplementary information files.”
No new data generated: “No new data were generated or analysed in this study.”

Avoid “available from the corresponding author upon request” as a stand-alone statement — most major publishers now explicitly reject it unless paired with a stated legal or ethical constraint.

Common mistakes that undermine reproducibility

Vague “upon request” wording used as a default, not an exception. A 2022 mixed-methods study in the Journal of Clinical Epidemiology (Gabelica, Bojčić & Puljak) examined 3,556 articles across 333 open-access journals with mandatory DAS policies and found “available on reasonable request” was the single most common DAS category — and, testing that promise directly with corresponding authors, found many were not in fact compliant with what their own published statement said. A DAS that isn’t backed by a data source someone can actually retrieve doesn’t support reproducibility, even when it satisfies a journal’s format requirement.
A repository link with no persistent identifier — plain URLs rot; DOIs and accession numbers are designed not to.
A statement that no longer matches the deposit — common when an accession number is issued after the statement was drafted and never updated in the final version.
Covering data but not the code needed to reproduce the analysis, where the analysis itself is non-trivial enough that the raw data alone isn’t sufficient to check the result.

Frequently asked questions

What must a data availability statement include?

At minimum: where the data can be found (repository name plus a persistent identifier such as a DOI or accession number), any conditions or restrictions on access, and — if access is restricted — the legal or ethical basis for the restriction and an institutional contact for requests. Clinical trial manuscripts submitted to ICMJE-following journals have additional required elements, including whether individual participant data will be shared and under what access criteria.

Do all journals require a data availability statement?

No — there is no single universal mandate. But requirements are broad and growing: PLOS journals, ICMJE-following journals (for clinical trials), Springer Nature/Nature Portfolio journals, and the more than 1,100 journals that have adopted at least one Center for Open Science TOP Guidelines standard all require one in some form. Outside journals with a formal requirement, including a DAS is increasingly treated as good practice regardless.