A data availability statement (DAS) reading “not applicable” is defensible only in narrow, specific circumstances — chiefly when no new data were generated or analysed, when data are proprietary clinical or commercial records, or when a legal or ethical restriction genuinely blocks disclosure. Outside those cases, “not applicable” is increasingly flagged by editors and funders as a red flag rather than a compliant statement.
A data availability statement is a mandatory or recommended manuscript section, usually placed before the references, that tells readers where the data underpinning a study’s findings can be found and under what conditions they can be accessed. Since most major publishers (Springer Nature, Wiley, Taylor & Francis, PLOS) now require a DAS on every research article, “not applicable” has become one of the most commonly misused entries in it — and one of the most commonly queried at copyediting or peer-review stage.
- When is “not applicable” a defensible data availability statement?
- When does “not applicable” trigger an editorial or funder query?
- “Available on request” versus “not applicable”: are they the same thing?
- How do funder data-sharing mandates change the calculus?
- Answer-first Q&A
- Implications for research administrators
When is “not applicable” a defensible data availability statement?
“Not applicable” is defensible when it is factually true that no dataset exists to disclose. Taylor & Francis’s author-services template lists this explicitly as one option among many, with the standard wording: “Data sharing is not applicable to this article as no new data were created or analyzed in this study.” Springer Nature uses near-identical phrasing for theoretical and mathematical papers that involve no empirical dataset.
Three case types consistently pass editorial and funder scrutiny:
- No new data generated. Review articles, theoretical papers, editorials, commentaries, book reviews, and hypothesis or proposal papers that synthesise existing literature rather than produce new datasets.
- Genuinely proprietary or clinical data under contractual control. Data held by a third-party sponsor, clinical trial data governed by a data-use agreement the author cannot unilaterally waive, or commercially embargoed findings pending patent filing.
- Data restricted by law or binding ethics approval. National statistical agency microdata, patient-level clinical records where the original informed-consent language did not cover public sharing, or datasets covered by data-protection legislation such as UK GDPR.
When does “not applicable” trigger an editorial or funder query?
“Not applicable” triggers a query whenever a study plainly did generate or analyse data but the statement fails to say why access is restricted. PLOS’s data-availability policy, in force for all research articles submitted since March 2014, states that the “not applicable” exemption applies only to article types that structurally contain no dataset — not to empirical studies that simply prefer not to share.
Cranfield University’s research-data-management guidance explicitly names “Availability of data and materials: ‘Not applicable'” as an example of an unclear statement when used on an empirical paper, because it gives the reader no route to verification. That is the core distinction editors are trained to apply: “not applicable” answers “does a dataset exist?”, not “will you share it?” Using it to avoid disclosing data that does exist — without stating a legal, ethical or commercial restriction — is what draws a production-stage or peer-review query.
| Statement pattern | Typically accepted? | Why |
|---|---|---|
| “Not applicable — no new data generated” | Yes | Factually verifiable from article type |
| “Not applicable” on an empirical/quantitative study | No — triggers query | Data exists; statement misrepresents the situation |
| “Data available on request from the corresponding author” | Conditional | Only under Basic or Share-Upon-Request publisher policies; must name the restriction |
| “Data not available due to [named] ethical/legal/commercial restriction” | Yes | Restriction is stated and attributable |
| Silence / statement omitted entirely | No — triggers query | Most publishers now mandate a DAS on every submission |
“Available on request” versus “not applicable”: are they the same thing?
No — they answer different questions and are not interchangeable. A data availability statement upon request concedes that a dataset exists but sets a conditional access route (typically via the corresponding author), whereas “not applicable” asserts that no dataset exists at all. Taylor & Francis restricts “available on request” wording to journals operating under its Basic or Share Upon Reasonable Request policies; it is not a universal fallback.
Editors increasingly scrutinise “available on request” statements too, following widely reported non-responsiveness rates in follow-up author contact — a dynamic documented in reproducibility literature and discussed on researcher forums such as Reddit’s r/AskAcademia. A defensible “on request” statement names the corresponding author’s role, the reason data are not openly deposited (privacy, participant consent, third-party licence), and — where a repository embargo applies — the release date.
How do funder data-sharing mandates change the calculus?
Funder policy increasingly overrides publisher-level flexibility on “not applicable.” Under the NIH Data Management and Sharing Policy, effective for all applications submitted on or after 25 January 2023, NIH-funded research that generates scientific data must include a Data Management and Sharing Plan — “not applicable” is only accepted where the award genuinely produces no scientific data (e.g. some career-development or infrastructure awards).
In the UK, UKRI’s Common Principles on Data Policy and the underlying Concordat on Open Research Data set an expectation that publicly funded research data be made as open as possible, as restricted as necessary — meaning a “not applicable” statement on a UKRI-funded empirical study should be paired with a funder-facing data management plan explaining the exemption, not left to stand alone. The ICMJE data-sharing statement requirement, in effect for clinical trials that began enrolment on or after 1 January 2019, similarly mandates a specific data-sharing statement in the trial registration and the manuscript; a bare “not applicable” does not satisfy it for an enrolling trial.
- Check the specific funder mandate before defaulting to “not applicable” — publisher policy and funder policy are separate compliance layers.
- Where a funder plan exists (e.g. an NIH DMS Plan or a Horizon Europe data management plan under cOAlition S expectations), reference it rather than repeating a bare exemption.
- For systematic reviews specifically, a data availability statement for systematic review should confirm whether extracted data tables, search strategies, or code are available, even though no primary dataset was generated — “not applicable” applies only to the absence of new primary data, not to the review’s own extraction materials.
Answer-first Q&A
What do you write in a data availability statement?
A compliant data availability statement names where the data live (repository, supplementary file, or “not applicable” with a reason), includes a DOI or accession number where one exists, and states any access conditions. Reviews, theoretical papers, and studies with no new dataset should say so explicitly rather than leaving the section blank.
What is the data availability statement data not available?
A “data not available” statement means the underlying data exist but access is restricted — for ethical, legal, or commercial reasons — and the restriction must be named. This differs from “not applicable,” which asserts no dataset was ever created. Conflating the two is the single most common cause of an editorial query at submission or production stage.
What does data availability mean?
Data availability describes whether, and how, the dataset behind a study’s findings can be accessed by readers and reproducibility auditors. Publishers including Springer Nature and PLOS treat the statement as a mandatory element of the peer-review record, on equal footing with author contributions and conflict-of-interest disclosures.
Implications for research administrators
Research offices and library data-management teams are best placed to catch a misapplied “not applicable” before submission, because they hold institutional visibility across a researcher’s funder obligations that a single-article editor does not. A pre-submission check against the relevant funder’s data policy — UKRI, NIH, or a Horizon Europe grant agreement — will catch the majority of cases where “not applicable” would otherwise be accepted by a publisher’s automated submission system but later queried by a funder compliance audit.
As funder data-sharing mandates tighten and publishers add automated DAS-completeness checks at submission, the margin for a generic “not applicable” will keep narrowing. Authors and administrators who document the specific reason — no new data, named legal restriction, or named commercial embargo — will clear both editorial and funder review; those who use it as a default will increasingly find it queried, not accepted.
For related terminology, see the CASRAI Research Glossary and the CASRAI-originated CRediT contributor role taxonomy, now stewarded by NISO as ANSI/NISO Z39.104-2022, which governs how data-curation and formal-analysis contributions are credited alongside data availability disclosures.
