Data Availability Statement Generator
Write the data availability statement journals now require. Tick where your data are — a repository, the supplement, restricted access, on request, or nowhere because none were generated — fill in the details, and copy the statement, with an optional code availability statement. Runs entirely in your browser — nothing is uploaded.
Your statements
Tick at least one case above to build the statement.
How to Use the Data Availability Statement Generator
- 1. Tick where the data are. Choose every case that applies — a study can have survey data in a repository and interview transcripts under restricted access. No data were generated stands on its own and clears the rest.
- 2. Fill in the details. Give each repository deposit its DOI or accession number. A DOI is turned into an https://doi.org/ link automatically; an accession number is printed as you type it.
- 3. Add a code statement if you need one. Choose how your code is shared, or that no custom code was written.
- 4. Fix the flags and copy. Anything you leave blank appears as a bracketed placeholder such as [repository name], and the notes under the result point out policy problems. Copy each statement into your manuscript or the submission form.
What a Data Availability Statement Is and Who Requires It
A data availability statement tells readers where the data behind a paper's findings can be found and how to get them — or why they cannot. Most large publishers now ask for one with every research article, but their policies are not identical, and the strictest wording wins when you submit.
| Publisher | What its policy asks for |
|---|---|
| Springer Nature | All original articles must include a data availability statement. Data in repositories should be cited with links and persistent identifiers (a DOI or accession number), and any restriction on sharing must be explained. |
| PLOS | All data needed to replicate the findings must be publicly available at publication. Restricted data are allowed only with a reason and a non-author contact, such as a data access or ethics committee. |
| Wiley | Each journal adopts one of four policies: Encourages, Expects, Mandates, or Mandates and Peer Reviews Data. From Expects upward, authors must state where their data are or that they are not available. |
| Taylor & Francis | Journals use one of five data sharing policies, from Basic (sharing encouraged) through Share Upon Reasonable Request, Publicly Available and Open Data to Open and FAIR. |
| Elsevier | Most journals build the data statement inside the submission system, where you can also give a reason the data cannot be shared — for example, that they are confidential. It is published with the article. |
Policies are set journal by journal. Treat this as orientation and check your target journal's instructions for authors before submitting.
Code has its own statement at some journals. Nature Portfolio journals, for example, require a separate Code availability section, placed after the data availability statement, whenever custom code or a mathematical algorithm is central to the conclusions.
Example Statement
Press Try an example to load a survey study whose anonymized responses are deposited openly while its interview transcripts stay restricted, with analysis code in Zenodo. The generator writes:
Data availability
The data that support the findings of this study (anonymized survey responses) are openly available in the Open Science Framework at https://doi.org/10.17605/OSF.IO/EXAMPLE. They are shared under the CC BY 4.0 license. Access to the interview transcripts is restricted to protect the privacy of the research participants. Requests for access can be made to the Research Data Office of the University of Eastbrook ([email protected]). Access is subject to a signed data use agreement.
Code availability
The code used in this study (R scripts for the analyses) is openly available in Zenodo at https://doi.org/10.5281/zenodo.example. It is released under the MIT license.
The identifiers in the example are illustrative. Notice the order: open data come first, restricted data next, and a sentence about the article itself last — on its own that sentence says "All data … are available within the article", and after other cases it becomes "Other data", so the statement never contradicts itself.
Common Mistakes
- Defaulting to "available on request". It is the easiest sentence to write and the one journals trust least. PLOS does not accept an author as the only route to restricted data, and many funders expect deposit. Use it only when there is a real reason, and say what the reason is.
- Linking to a repository, not to the data. "Available on Zenodo" sends readers to a search box. Give the dataset's own DOI or accession number.
- Forgetting reused data and code. Springer Nature asks the statement to cover secondary data you analyzed as well as data you generated. If the conclusions depend on custom code, say where it is too.
- Claiming everything is in the article. "All data are available within the article" is only true when the supplement really holds the underlying data, not just summary tables.
- Submitting placeholders. Every [bracketed] item in the output is a gap. Replace each one before you paste the statement into a submission form.
Frequently Asked Questions
- What is a data availability statement?
- It is a short section of a research article that says where the data supporting the findings can be accessed — usually a repository with a DOI or accession number — or explains why the data cannot be shared and how they can be requested. Many publishers make it a condition of publication.
- Is "data available on request" acceptable?
- Sometimes, but not everywhere. Taylor & Francis has a Share Upon Reasonable Request policy and Wiley offers a template for it, while PLOS requires public availability and will not accept an author as the only contact for restricted data. Check your journal's policy, and give a reason when you use it.
- What do I write if my study did not generate any data?
- Say so plainly: "Data sharing is not applicable to this article, as no datasets were generated or analyzed during the current study." For purely theoretical work, the generator can instead state that the article reports theoretical work and that no data were generated or analyzed.
- Do I need a separate code availability statement?
- If your conclusions depend on custom code, often yes. Nature Portfolio journals require a Code availability statement after the data availability statement in that case, and other journals ask for code in the same statement as the data. Archive the code in a repository that issues DOIs rather than linking to a GitHub page that can change.
- Which repository should I deposit my data in?
- Use a discipline-specific repository when one exists for your data type, such as the Gene Expression Omnibus for gene expression data, and a general repository such as Zenodo, Dryad, Figshare or the Open Science Framework otherwise. PLOS strongly recommends repository deposit, and many journals list the repositories they accept in their instructions for authors.
- How do I share data that contain personal information?
- Usually through restricted access: de-identify what you can, deposit or hold the data where an access committee can review requests, and state the conditions of access in the statement. Choose the restricted case in the generator and name the committee or office that handles requests.