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Preserve research data

Research data is a valuable resource and sharing data after a project completes has many benefits, including:

  • creating potential for new collaborations
  • encouraging transparency in research practices
  • reducing the cost of further data collection

All research data you share must conform to the University’s Research Code of Practice. Guidelines and support on ethics can be found from Research and Impact Services. This section will help you with:

When not to share

Where appropriate, it is good practice to make your research data available to a wider audience, but in some cases it is necessary to restrict access to research data for security, confidentiality or commercial reasons. For example:

  • the data is covered by GDPR and is subject to the consent granted by the participants to whom it relates

  • the data has been obtained under a non-disclosure agreement from a partner

  • access to the data has been purchased from a commercial provider

  • the data may lead to a commercial opportunity/patent

Appropriate safeguards need to be in place before sensitive or confidential data can be shared. Some repositories provide a facility to control access to data. Here is a list of repositories that provide restricted access options. You can also search using the “restricted access” filter.

Some data centres apply physical access conditions to their datasets. The University of Warwick is establishing a SafePod service, enabling local researchers to access many such datasets in the University of Warwick library.

Retention of your data

The Digital Curation Centre has a list of research funder requirements on how long research data should be stored after the end of the project. If your funder is not on this list please use the Sherpa Juliet service to check if your funder has any requirements for research data.

The University of Warwick’s Research Data Management Policy is designed to allow all Warwick researchers to be compliant with all known funder requirements.

Selecting data for long term curation

Not all research data is suitable for long term preservation.

The DCC has created a comprehensive guide to appraising and selecting data for preservation - five steps to decide what data to keep; and you may wish to seek individual guidance offered by your research funder.

Choosing a data archive for your data

Once you’ve decided what data you need to keep in the long term you will need to choose where to deposit this data to make it available.

The advantages of depositing your data with a repository include:

  • a permanent public record will be created to enhance the discoverability of your data
  • your data will be assigned a persistent identifier (e.g. DOI) making it easier for you and others to cite your data in publications
  • compliance with funder, journal and/or institutional data policies

Subject specific repositories have expertise and the resources to manage specific types of data. You can search for a repository by subject using the Registry of Research Data Repositories.

Your funder may also support or recommend a particular repository, for example:

Some publishers have also published lists of recommended data repositories:

If no discipline-specific repository or community resource is available, you can find a list of recognised general-purpose data repositories on the Wellcome website.

Licensing your research data

Licensing allows you to specify what people can and cannot do with your data. It makes clear how you intend others to reuse or share your data. The permissions you give to others will come in the form of a copyright licence. Your funder may require certain conditions for access and reuse of your data.

If you don't use a licence, it won’t be clear how you intend your work to be reused.

Applying a licence makes your intent clear and places the obligation to respect your wishes and rights on the user.

It is best to have an idea which license you plan to use before you start collecting data. This can help in planning consent requests from research participants.

There are specialist data licenses and the tools below can help you choose the most appropriate licence for your data/software.

Data access statements

Data access statements, also known as data availability statements, are included in publications to describe where the data associated with the paper is available, and under what conditions the data can be accessed. They are required by many funders and scientific journals as well as the UKRI Common Principles on Data Policy.

The aim of the data access statement is to promote the discoverability of research data that has been created in the life of a project.

What to include

Examples of data access statements are provided below, but your statement should typically include:

  • where the data can be accessed (preferably a data repository)
  • a persistent identifier, such as a Digital Object Identifier (DOI) or accession number, or a link to a permanent record for the dataset
  • details of any restrictions on accessing the data and a justifiable explanation (e.g. for ethical, legal or commercial reasons)

Examples of data access statements

Openly available data

All data underpinning this publication are openly available from [REPOSITORY NAME] at [DOI, ACCESSION NUMBER OR URL].

Embargoed data

"All data underpinning this publication will be available from [REPOSITORY NAME] at [DOI, ACCESSION NUMBER OR URL] from [date] onwards, following the cessation of an embargo period."

Restricted data

"Due to ethical/commercial issues, data underpinning this publication cannot be made openly available. Further information about the data and conditions for access are available from at [DOI, ACCESSION NUMBER OR URL] Access to the data is subject to approval due to (GIVE REASONS WHY ACCESS TO THE DATA IS RESTRICTED).”

Physical data

"Physical data supporting this publication are stored by the University of Warwick. Details of the data and how it can be accessed are available from [REPOSITORY NAME] at [DOI, ACCESSION NUMBER OR URL].

Secondary data

"Pre-existing data underpinning this publication are available from [REPOSITORY NAME] at [DOI, ACCESSION NUMBER OR URL] Further information about data processing, and additional new supporting data are available from at [DOI, ACCESSION NUMBER OR URL].

No new data created

"No new data were created during this study.”

No data

"This work is entirely theoretical, there is no data underpinning this publication."

Standard data citation

The standard citation format for a dataset recommended by DataCite:

Creator(s) (Publication Year): Title. Publisher. Resource Type. Identifier

For example:

Lockey, Christine, Young, Hannah, Brown, Jessica and Dixon, Ann M. (2022) Data for Characterization of interactions within the Igα/Igβ transmembrane domains of the human B-cell receptor provides insights into receptor assembly. [Dataset]

Where to get further help

Contact researchdata at warwick dot ac dot uk for further help or advice.