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Reuse & Cite Data

Take previous research one step further.

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Reuse data

Existing research data can be used in increasingly diverse ways to extend the findings of previous research as well as address new research questions. The way you can reuse the data will depend on a number of factors:

  • licensing and reuse terms for any dataset.
  • consent of the original participants.
  • relative risk of re-identification of participants if you are combining data sources.
  • quality of the metadata and documentation to support the understanding of the data.
  • availability of the software or code used to create the data.
  • ability to open the files and possibly convert the formats.

Additional checks will need to occur if you are obtaining identifiable data. Ensure the transfer, management and storage have been considered through a data management plan and ethical review before obtaining the data.

Secondary analysis will vary according to the nature of the data and you’ll need to plan your methodology carefully.

Citing data you reuse

Make sure dataset creators receive appropriate credit for their work, just as you would for other research outputs.

The DataCite initiative and FORCE11 are creating standards in this field. Where available, include a unique identifier (e.g. DOI), for the data. Where a DOI or citation isn’t provided, apply best efforts by including authors, year, data title, version, publisher and identifier.

The Digital Curation Centre have created guidance on citing physical data. 

There is no set way of citing data, but there may be guidance in the referencing style for your discipline. If youa re using reference management software (e.g. EndNote), types of data may be listed as information types, with a style applied. You can also explore the library's self-paced courses for referencing and EndNote.

Citing your own data

Whether you have primary or a modified version of secondary data, you should include a link to this data within research outputs. This is often called a data access statement and many funders and publishers require this.

Undertaking this activity will add datasets to the repositories outlined and allow reuse where possible. Ultimately this is for the benefit of everyone as it speeds up research and increases the efficiency of collected data.