You can use research data to interrogate or extend the findings of previous research, as well as to address new research questions. Data reuse is also known as secondary analysis.
Secondary analysis may yield a number of academic benefits but it can be difficult and time consuming. You will need to plan your methodology carefully.
The way you can reuse data will vary according to the nature of data – for example, whether it is quantitative or qualitative.
Things to consider before reusing data
Here are some areas to consider. This is not a comprehensive list.
- The licensing and reuse term for any dataset: can you perform the analysis you wish to and can you disseminate the results?
- What consent have the original participants given? Is it sufficient for your own research or is further consent required?
- Is there any risk that anonymized participants could become identifiable – for example, if you are combining datasets from more than one source?
- What metadata and documentation is available? Is it sufficient to support understanding and reuse of the data?
- What data formats have been used? Is it appropriate do convert data to a common file format?
- Does the data source provide any guides and tools to help you explore and manipulate data?
Don’t forget to maintain the integrity of the original data; always save a new version.
Make sure you store any sensitive data appropriately. See the University’s Information Protection Policy for further details.
Key ethical and legal considerations are addressed on the Research and Innovation Service website.