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IOP Science

IOP Publishing open data policy

Open data: helping you maximise the impact of your research

Publishing your research data alongside your article helps other researchers understand, validate and build on your work. It can increase the visibility of your research and support transparency, making it easier for others to cite and reuse your findings. Our open data policy is designed to help you share your data easily to benefit you and your research community.

This policy applies to Environmental Research: Climate, Environmental Research: Ecology, Environmental Research: Food Systems, and Environmental Research: Water, Machine Learning: Science and Technology, Machine Learning: Engineering, Machine Learning: Earth and Machine Learning: Health. For other IOP Publishing journals, please refer to the relevant data availability policy for your journal.

Please note that the majority of IOP Publishing journals have adopted our research data availability policy. The ‘about the journal’ section on each journal’s website will confirm which research data policy applies.

What you need to do

To support reproducibility and transparency, you will need to make available the research data needed to verify or reproduce the results reported in your article. This data should be publicly accessible when your article is published.

We recommend that you:

  • Deposit your data in a trusted repository.
  • Use a repository that assigns a persistent identifier, such as a DOI.
  • Choose a licence that enables others to reuse your data where appropriate.
  • Follow FAIR principles to make your data findable, accessible, interoperable and reusable.

If legal, ethical or confidentiality considerations prevent data from being shared openly, we will work with you to ensure appropriate access arrangements are explained clearly in your article.

Author responsibilities

Authors are solely responsible for the accuracy, integrity and legal compliance of any data shared via third party platforms. Editors will evaluate the manuscript’s data availability statement to determine whether the authors have adhered to the journal’s data sharing policy and may request to see data as part of the review process.

Why share your data?

Making your data available benefits both your research and the wider community. Sharing your data can help you:

✅ Increase trust in your research

✅ Improve the reproducibility of your findings and enable new discoveries by allowing others to build on your work

✅ Increase the visibility and potential impact of your research

✅ Create opportunities for data citation and reuse

✅Contribute to a more open and collaborative research environment

What counts as research data?

You should make available any research data required for others to verify or reproduce the results reported in your article. This may include:

  • Datasets and spreadsheets
  • Software and code
  • Images and figures
  • Audio and video files
  • Maps
  • Raw and processed data
  • Documents and supporting materials

This includes both data you have generated yourself and data from other sources that underpin your study’s findings.

How to choose a repository for your data

We encourage authors to deposit their data in a trusted repository that is appropriate for their discipline, please see subject specific repositories here. Further repositories can be found via https://www.re3data.org/.

A suitable repository should:

  • Preserve data for the long term
  • Provide a persistent identifier such as a DOI
  • Support data citation
  • Make data discoverable and accessible
  • Offer appropriate access controls where necessary

If no subject-specific repository is available, general repositories such as Zenodo, Figshare or Dryad may be suitable alternatives.

You should make available the data that is needed for others to understand, verify or reproduce the findings reported in your article. 

This does not necessarily mean sharing every file created during your research project. The focus is on the data that supports the results and conclusions presented in your article. 

The data supporting your article should be publicly accessible when your article is published. 

Many repositories allow you to deposit data before publication and keep it under embargo until your article is published. 

We recommend depositing your data in a trusted repository that is appropriate for your discipline. Many researchers choose a subject-specific repository, while others use a general-purpose repository. 

Examples of widely used repositories include: 

  • Zenodo – a multidisciplinary repository for datasets, software, publications and other research outputs. 
  • Figshare – a general-purpose repository for sharing and citing research data and supporting materials. 
  • Dryad – a curated repository for research datasets across a range of disciplines. 
  • PANGAEA – a repository for earth, environmental and geoscience data. 
  • Environmental Information Data Centre (EIDC) – a repository for environmental science data. 
  • GenBank – a repository for nucleotide sequence data. 
  • GitHub (with Zenodo integration) – commonly used for sharing software, code and workflows. 

If you are unsure which repository is most appropriate for your research, repository discovery tools such as re3data.org can help you identify suitable repositories for your discipline. 

Your chosen repository should ideally: 

  • Provide a persistent identifier such as a DOI. 
  • Support long-term preservation. 
  • Enable data citation. 
  • Make data discoverable and accessible. 
  • Offer appropriate access controls where needed. 

If no suitable subject-specific repository exists, a general-purpose repository such as Zenodo, Figshare or Dryad is usually an appropriate option. 

We recognise that it is not always possible to make research data publicly available. 

Reasons may include: 

  • Ethical restrictions 
  • Privacy or confidentiality concerns 
  • Legal or contractual obligations 
  • Commercial sensitivity 
  • National security considerations 

If data cannot be shared openly, you should explain the reason in your manuscript and, where possible, indicate how access may be requested or provided under controlled conditions. 

If your research includes personal, confidential or sensitive information, you should ensure that any data sharing complies with relevant ethical and legal requirements. 

In some cases, data can be anonymised and shared. In others, access restrictions may be necessary. If data cannot be shared openly, this should be explained in your manuscript. 

If your study relies on data obtained from another organisation, institution or data provider, you may not have permission to share that data. 

In these cases, you should provide details of the source of the data and explain any restrictions on access. Where possible, you should also explain how other researchers may request access from the data owner. 

Yes. Code, software and scripts that are required to reproduce your results should be shared wherever possible. 

We encourage you to deposit code in a trusted repository and provide a persistent identifier to support citation, reuse and reproducibility. 

The journal requires all authors to include a data availability statement in their article. Provision of a data availability statement is a condition of publication.

A data availability statement explains where the data supporting the results reported in the article can be found. Where applicable, it should include links or persistent identifiers for publicly archived datasets generated or analysed during the study.

If your research data cannot be made publicly available, you will be asked during the submission process to explain why. If the editors determine that the reason justifies an exception to the policy, this explanation will be published as part of the data availability statement.

Please note that stating that data will be made available “upon request” is not sufficient to meet the journal’s research data sharing requirements.

If the research data is contained within the article’s supplementary files, select the relevant data availability statement during submission. IOP Publishing will add the dataset’s Digital Object Identifier (DOI) during the production process.

You will be able to review your data availability statement during proof correction. Data availability statements cannot be amended after publication.

At submission, authors will be asked to provide the DOI, pre-registered DOI, hyperlink, or other persistent identifier associated with the research data supporting their article.

If you provide a pre-registered DOI, you should be prepared to supply a reviewer access URL if requested during peer review.

We encourage authors to make research data available under open licences that permit reuse wherever possible, such as CC0.

The journal does not require a specific licence for datasets deposited in third-party repositories, and the publisher does not claim copyright in research data.

Research data submitted as supplementary files will be published under the same licence as the article, and authors will retain copyright.

Where possible, research data should be shared using open, non-proprietary file formats that can be accessed without specialist commercial software.

For example, tabular data should ideally be shared as CSV files rather than XLS or XLSX files. Using open formats helps make data more accessible, reusable and sustainable over the long term.

Datasets should be formally cited in the reference list of your article in the same way as other research outputs.

Providing a formal data citation helps ensure that datasets receive appropriate credit and makes it easier for others to find, access and reuse your data.

No. Sharing research data in line with this policy supports transparency and reproducibility and will not negatively affect editorial decisions.

If there are legitimate reasons why data cannot be shared openly, these will be considered during the publication process and appropriate alternatives can usually be accommodated.

FAIR principles are a set of guidelines that help make research data more useful and reusable.

FAIR stands for:

  • Findable – data can be discovered and identified by others.
  • Accessible – data can be obtained using clear procedures.
  • Interoperable – data can be used with different tools, systems and workflows.
  • Reusable – data is well described and can be used in future research.

Following FAIR principles helps maximise the visibility, impact and long-term value of your research data.

If you are unsure how to comply with this policy or need advice on sharing your data, please contact the journal’s editorial office or the IOP Publishing support team. We are happy to help you identify an appropriate solution for your specific circumstances.

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