Guidelines for Data Availability Statements in Physical Review
Sharing data and software supports the independent verification of findings, allows further analysis, and helps ensure transparency and trust in published literature. Open data and software are also increasingly required in institutional and funder policies.
Overview of Policies
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Statement required: All published articles must include a Data Availability Statement (DAS). Authors are asked to enter a statement that describes the availability of relevant data and software during the submission process. See Crafting Data Availability Statements for guidance on writing your statement.
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Data sharing encouraged: Authors are strongly encouraged to share data and software publicly and according to FAIR (Findable, Accessible, Interoperable, Reusable) principles at publication.
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Citation required: Publicly shared data and software must be cited in the reference list, and the citation must be included in the data availability statement.
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Embargoes permitted: Embargoes on public data sharing are allowed for reasons like privacy or trade secrets. Include details of any embargo within your statement.
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When data aren’t available: If data can’t be made public, authors must agree to share data privately with editors, reviewers, and readers upon reasonable request. Authors should also provide a reason or further information in their statement.
What Qualifies as Research Data?
Research data and software includes any factual material necessary to verify or replicate study results:
- Tabular data
- Code and software created by the authors
- Photographs and images that aren’t available in digital form
- Audio and video files
- Documents
- Raw and/or processed data
Exclusions: personal, sensitive or otherwise prohibited data must not be shared unless consented for release.
Alternatives include:
- Depositing in controlled access repositories
- Anonymizing data
- Sharing metadata only
- Outlining access procedures in the data availability statement
Data Sharing Best Practices
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Preferred Method: Use established data repositories to ensure data is Findable, Accessible, Interoperable, and Reusable (FAIR).
- Recommended Repositories:
- Zenodo
- Dryad
- Figshare
- Harvard Dataverse
- OSF
- Your institution or funder repository
- Avoid: Using Supplemental Material files or personal websites for data sharing, as they lack unique identifiers, relevant metadata, and may not align with FAIR principles.
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Formats: Use open, non-proprietary formats (e.g., CSV instead of XLS).
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Standards: Adopt community-recognized data standards; refer to FAIRsharing for guidance.
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Licensing: Open licenses are encouraged, but APS does not mandate specific licenses for data in third-party repositories.
Data Citation Requirements
Publicly available data must be cited in the reference list with:
- Authors
- Data or software name
- Year of publication
- Version number (if applicable)
- Repository/Archive name
- Persistent identifier (preferably DOI)
If the data is associated with an article in a data journal, include that as a separate journal reference.
For example:
[1] J. Smith and S. Brown, Quantum Material Josephson Diode Measurements, Version 1.2, [Dataset], Dryad, 2021, https://doi.org/10.5061/dryad.abcdef123.
[2] J. Smith and S. Brown, Q-Diode Analytics, Version 3.11, [Software], Zenodo, 2020, https://doi.org/10.5281/zenodo.1234.
Submission Process
- Enter a complete data and software availability statement during the submission process, including relevant citations.
- If you’ve already included a statement in your manuscript, copy it into the submission form. This ensures easy checking and use by editors, reviewers, and our production team.
- Amend the statement as necessary during revision or proofing.
- Your statement will be visible to editors and reviewers, who may comment on the statement during review. The statement will be included in the published article.
Crafting your data availability statement
A data and software availability statement should describe clearly and concisely how the data and/or software used in your research can be accessed, including references. Include details about all relevant data.
If you answer yes to any of the following questions, make sure that your data statement reflects the availability of the data or software. Most authors will answer “yes” to at least one of these questions.
- Are you reporting original measurements (e.g., in the form of plots)?
- Are you reporting an original analysis of pre-existing measurements (e.g., in the form of plots)?
- Are you reporting an original numerical calculation (e.g., in the form of plots)?
- Are you utilizing original code, software or notebooks such as Mathematica and Jupyter?
Here are some examples of statements:
| Scenario |
Examples of Data Availability Statements |
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Data is publicly available
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- The data that support the findings of this article are publicly available [1,2].
- The data used to generate figure 1 are available from Ref. [1], and data for figures 2, 3, and 4 are available from Ref. [2].
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Software is publicly available
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- The code used to analyze the data is available from Ref. [1].
- The data that support the findings of this study were generated by numerical simulations. The source code and parameters used to generate the simulations is publicly available [1].
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Data is available, but subject to application or big data policy
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- The data that support the findings of this article are publicly available by application subject to the policy of the <collaboration/experiment/institution> [1].
- The data behind the plots is publicly available from HEPdata [1], with analysis software available from [2]. The broader datasets that were used are not publicly available, and subject to access according to [policy] [3].
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Data is available after embargo
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- The data that support the findings of this article are publicly available [1,3], embargo periods may apply.
- The data that support the findings of this article will be publicly available after embargo from 31 December 2028 from Ref. [1].
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Data in supplemental material
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- The numerical values for data shown in Figs. 1 and 2 are given in Table I and for data shown in Fig. 3 are given in Table II in the supplemental material.
- [Note: sharing data in supplemental material is not recommended.]
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Some data is publicly available, some not
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- Some of the data that support the findings of this article are publicly available [1,2,3]. <dataset 1> and <dataset 2> cannot be made publicly available because they contain commercially sensitive information. The data are available upon reasonable request from the authors.
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Software/code is partially available
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- <software name> was used to analyze the data in this article. The custom scripts used in the analysis are available [1], but the software package is not publicly available due to licensing conditions.
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If data or software are not publicly available, we provide a default statement you can choose at submission. However, we encourage you to expand on this by providing a reason and indicate future availability plans if applicable.
| Scenario |
Examples of Data Availability Statements |
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No data publicly available, all of them unavailable for the same reason
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- The data that supports the findings of this article cannot be made publicly available because <reason>. The data are available upon reasonable request from the authors.
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For example:
- The data that supports the findings of this article cannot be made publicly available because they contain commercially sensitive information.
- The data that supports the findings of this article cannot be made publicly available because the data or software is owned by a third party, and public sharing rights have not been secured.
- The data that supports the findings of this article cannot be made publicly available because they contain sensitive personal information.
- The data that supports the findings of this article cannot be made publicly available because the data is too large and no suitable public repository exists for hosting in this field of study.
- The data that supports the findings of this article cannot be made publicly available due to institution/funder/collaboration policy [1].
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No data publicly available, different datasets unavailable for different reasons
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- <Dataset 1> cannot be made publicly available because the data is too large and no suitable public repository exists for hosting in this field of study. <Dataset 2> cannot be made publicly available because they contain commercially sensitive information. The data are available upon reasonable request from the authors.
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No data publicly available at publication, but will be in future
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- The data that supports the findings of this article cannot be made publicly available because they are under an embargo until <date> according to <policy>. The data are available upon reasonable request from the authors.
- The data that supports the findings of this article will be made available once the current research plan is completed, expected by <date>. More information and data are available upon reasonable request from the authors.
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Data may not be available, is subject to institution or collaboration policy
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- Release and preservation of data used by <collaboration> is subject to the <policy name> [1]. The authors may be contacted for further information on data or software availability.
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Software is not available
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- The software used for this research is owned by a third party and cannot be publicly shared.
- <software name> was used to analyze data, however is subject to licensing conditions that prevent sharing.
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No data or software was created or analyzed
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- No data were created or analyzed in this study.
- This is a purely mathematical work and no data was created or analyzed in this study. All figures can be reproduced directly from the presented equations.
- This is a review article and no data was analyzed or software created.
- Note: this is typically only appropriate if your work is purely mathematical (e.g., deriving equations or showing a proof), or you’re reporting measurements that have already been presented elsewhere without analysis.
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Compliance and Post-Publication
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Access Issues: If readers can’t access data as described, please contact APS’ editorial office.
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Corrections: APS may issue corrections or expressions of concern if the published DAS no longer reflects data availability.
