Data Availability & Sharing Policy

Open science strengthens the research record. When the data, code and materials behind a study are shared responsibly, findings can be verified, reused and built upon — and authors receive credit for the effort that data creation represents. Directive Publications is an international open-access publisher, and our guiding principle for research data is simple: it should be shared “as open as possible, as closed as necessary.” That balance — endorsed by the wider scholarly community and reflected in the COPE Core Practices and the ICMJE Recommendations — recognises that maximal openness is the goal, while legitimate privacy, legal and ethical constraints are respected.

This policy applies to research published across all of Directive Publications’ peer-reviewed journals. It is aligned with the COPE Core Practices, follows the ICMJE Recommendations, and adopts the FAIR principles (Findable, Accessible, Interoperable, Reusable) as guidance. It complements our editorial policies, research integrity framework and author guidelines.

Scope and definitions

By underlying research data we mean the minimal dataset required to reproduce and independently verify the findings reported in the article — for example the measurements, observations, survey responses, images, sequences, model outputs or statistical inputs on which the conclusions rest. This is distinct from the article itself.

• A Data Availability Statement (DAS) is required for original research articles.
• Sharing is encouraged where relevant for reviews, case reports and other article types that draw on original data or materials. See article types for guidance by format.
• The peer-reviewed article is published Open Access under CC BY 4.0 and authors retain copyright (see open access and copyright). The data are a separate output, deposited independently and carrying their own licence chosen by the author or repository.

The Data Availability Statement (DAS)

Every research article must include a Data Availability Statement, which is published together with the accepted article. The DAS must state clearly where the data underlying the results can be found, in what repository or form, and under what access conditions. Authors should select the option below that best describes their situation and word the statement accordingly.

1. Open in a public repository. Data are deposited in a recognised repository and cited with a persistent identifier (a dataset DOI or accession number).
2. Within the article and its supplementary files. All data supporting the results are included in the manuscript and its supplementary materials.
3. Third-party or previously published data. Data were obtained from a named third party or prior source; the DAS names the source and gives the citation or access route.
4. Controlled-access data. Data are held under managed access; the DAS names the body that controls access and the procedure to request it.
5. Restricted for ethical or legal reasons. Data cannot be shared openly; the DAS states the specific reasons and how legitimate requests may be handled.
6. No new data. No new data were generated or analysed in the study.

A bare statement that data are “available from the corresponding author on reasonable request” is discouraged as the sole route. Deposit in a repository is expected wherever it is possible; the on-request wording is acceptable only when documented legal or ethical constraints genuinely prevent open deposit, and even then open metadata and an access procedure should be provided.

The FAIR principles

We ask authors to make data FAIR (the 2016 Guiding Principles). FAIR is guidance we follow, not a badge or certification. In practice:

• Findable — deposit data where they receive a persistent identifier and rich metadata, so others can locate them.
• Accessible — place data in an open or controlled-access repository with clear, stated access terms, retrievable by a standard protocol.
• Interoperable — use open, community-standard formats and vocabularies so data can be combined and understood across tools.
• Reusable — provide full documentation (a README, variable definitions, methods) and apply a clear data licence, for example CC BY 4.0 or CC0.

See the FAIR / GO-FAIR principles for the full definitions.

Choosing a trusted repository and persistent identifier

Directive Publications does not host or curate a data repository. We recommend that authors deposit with an independent, trusted third-party repository:

• Use a discipline-specific repository first. Where a recognised community archive exists for your data type (for example sequence, structural, crystallographic, proteomic or climate archives), deposit there and quote the accession number.
• Use a trusted generalist repository as a fallback when no domain repository fits — for example Zenodo, Dryad, figshare, Harvard Dataverse, OSF or Mendeley Data.
• Locate a suitable repository through re3data.org and FAIRsharing.org.

Datasets should carry a repository-minted dataset DOI (typically issued via DataCite) or a stable accession number. Please note the distinction: article DOIs are Crossref-registered by Directive Publications under prefix 10.52338, whereas the dataset DOI is minted by the repository you choose — the two are separate identifiers. Depositing files only as article supplementary material is a weaker option than a repository, because supplementary files are less findable and lack an independent identifier.

Sharing code, software and materials

Where custom analysis depends on code, we encourage a Code / Software Availability statement alongside the DAS. Best practice is to:

• Deposit custom code in a repository that issues a DOI (for example an archived release), released under a recognised open-source licence;
• Include documentation — dependencies, run instructions and version information — sufficient for reuse;
• Share unique materials, reagents and detailed protocols where feasible, so methods can be reproduced;
• State clearly, and justify, any code or materials that cannot be shared.

Legitimate exceptions — and how to word them

Openness is not absolute. Valid reasons to limit sharing include participant privacy and confidentiality, the limits of informed consent, legal or regulatory constraints, third-party or commercial licence terms, biosafety or dual-use concerns, and Indigenous data sovereignty. In these cases the honest approach is not silence but managed transparency:

• Deposit open metadata so the dataset is discoverable even when the data themselves are restricted;
• Provide de-identified or controlled-access data wherever possible;
• Name the body that controls access and give the procedure to request it.

Model wordings (replace the bracketed placeholders):

• Controlled access: “The data supporting this study are available from [ACCESS AUTHORITY] under a controlled-access agreement. Requests may be made to [CONTACT / ROUTE]; access is subject to [CONDITIONS].”
• Restricted for privacy/consent: “To protect participant privacy and within the limits of the informed consent obtained, the individual-level data cannot be shared publicly. De-identified data may be made available to qualified researchers on approval by [ETHICS BODY / ACCESS AUTHORITY]; the study metadata are openly available at [REPOSITORY / DOI].”
• Cannot be shared: “The data underlying this article are subject to [LEGAL / COMMERCIAL] restrictions and cannot be shared. Enquiries regarding the data should be directed to [ACCESS AUTHORITY].”

Data citation

Datasets that are used or generated should be cited in the reference list — not merely mentioned in the text — with the dataset’s author(s), year, title, repository or publisher, and its persistent identifier. This follows the FORCE11 Joint Declaration of Data Citation Principles and ensures that data producers receive formal, discoverable credit for their contribution.

Clinical trials and human-participant data

For clinical trials, authors must follow the ICMJE requirement for an individual participant data (IPD) sharing statement. The statement should indicate whether de-identified IPD will be shared, what data, which related documents (for example the protocol and statistical analysis plan), when and by what mechanism. Trials are expected to be prospectively registered, and shared participant data must be appropriately de-identified and consistent with the consent obtained. These expectations sit alongside our research integrity and publication ethics requirements.

Editorial handling and compliance

During double-blind peer review, editors and reviewers may request to see the underlying data to assess a manuscript. The DAS is checked for completeness and internal consistency with the methods and results. Where a statement is inadequate, unclear or inconsistent, editors may query the authors and request revision. Where a statement is found to be false or a serious data problem emerges after publication, editors may pursue a correction, an expression of concern or a retraction in line with our corrections policy and the COPE Core Practices.

Directive Publications does not independently re-run, validate or guarantee the reproducibility of every dataset or code submission, and we set no fixed turnaround times for these assessments. Our role is to require a clear, honest availability statement and to act, where warranted, through established, ethics-aligned processes. Submissions also undergo similarity screening, and ORCID is encouraged for all authors.

Preservation and long-term access of the published record

We take reasonable, transparent steps to safeguard the scholarly record, and we describe them without overstating what is currently in place:

• Every article is issued a persistent Crossref DOI (prefix 10.52338), providing a stable, resolvable identifier for the version of record.
• Article metadata are openly harvestable via OAI-PMH and available as JATS XML, so third parties can discover and index the content.
• We maintain regular secure off-site backups of the database and the full site, held in a separate location.
• All content is CC BY 4.0 licensed, which permits third parties to copy, archive and redistribute the work — open, DOI-identified content can, for example, be captured by services such as the Internet Archive.
• Directive Publications is actively pursuing a formal digital-archiving arrangement to further strengthen long-term preservation.

These measures are described as our current practice and forward plans; they are offered in good faith rather than as a guarantee. Our preservation policy carries further detail.

Author compliance checklist

1. Prepare the minimal dataset needed to reproduce your results.
2. Choose a repository (discipline-specific first, trusted generalist otherwise) and obtain a dataset DOI or accession number.
3. Apply a data licence (for example CC BY 4.0 or CC0) and add documentation.
4. Write your DAS using the category options and templates above.
5. Cite the dataset in your reference list with its persistent identifier.
6. Add a code availability statement if your study relies on custom software.

Related policies and contact

This policy should be read together with our author guidelines, editorial policies and research integrity framework. Authors preparing a submission can begin at submit your manuscript or browse our journals.

Questions about data sharing may be sent to [email protected], or by post to Directive Publications, 30 N Gould St, Sheridan, WY 82801, USA. This policy is reviewed periodically and updated as our practices and the wider standards evolve.