Data retention guidance

When deciding which of the data produced in your project should be stored for the long term, consider the following criteria. If you answer 'Yes' to any of these questions, you should archive the data.

  1. Does this version of the dataset support a publication?
  1. Does the University or your funder stipulate a retention period for the data?

Most funders expect you to provide at least the information that someone would need to be able to validate your published research as a minimum. For detailed requirements, check your funder's policy.

  1. Are you responsible for keeping the master copy (as its creator or owner)?

Try to find out if other copies of the data exist and are accessible and useable. If other copies exist, make sure the most comprehensive or up-to-date version is archived.

  1. Is the dataset unique and cannot be re-created?

Some data by their nature cannot be re-measured or re-created such. These include e.g. earth observations or people-based data. These datasets may often warrant indefinite storage and preservation.

  1. Would the data be useful in further research (by you or others)? Can they be re-used by others?

Make sure you provide enough documentation to support sharing, access and re-use of the data such as the context of the project, methodology, copyright/IPR and ethical issues. If your data was obtained from human subjects, ensure you obtained consent for archiving and re-use.

However, weigh up the costs and benefits, both in terms of time costs/curation and cash costs of storage and long term curation. In some cases, it might be cheaper to re-create the data than preserve them for the long term. Make sure that you provide enough information to re-create the data by e.g. preserving the generating code and environment.

Any decision to dispose of Research Data is the responsibility of the researcher, consulting with their College Director of Research and appropriate Professional Services staff, where appropriate. If Research Data are to be disposed of, then the reasons for doing so should be properly documented and stored as part of an updated data management plan for the project.

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Last updated: September 2020


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