Data Reuse, or Secondary Data Analysis, is the analysis of existing data collected by other individuals or institutions for a new research purpose. It can refer to statistical, quantitative data or descriptive, qualitative data.
Starting your own research from the existing data collected by other researchers can have some major benefits:
- much of the background work has already been completed making it easier to undertake further research
- it's time-saving and cost efficient due to the reduced cost assocaiated with duplication of data
- the data comes with a degree of pre-established validity and reliability
- potential for collaboration opportunities
However, careful consideration is required before reusing data. Make your search for data as efficient as possible by thinking about the following questions before you get started:
- Is there enough description about the content of the data? Is the context of the research relevant?
- Is the source trustworthy? Is it produced by a reputable organisation or researcher in the field?
- Do you know how long the data will be stored and made available?
- Which file formats am I able to work with? If you are planning on using analytical software, ensure you know the formats that are compatible.
Licenses and user agreements
- Are there restrictions or specifications of data reuse? For instance, if you plan on commercialising your research you should avoid datasets that have non-commercial conditions in their reuse licence.
- What will be the impact of these restrictions on your research?
Methodology
- What is the relationship between existing and new data?
- How will the data be integrated?
- How will any format differences be managed?
Considering these aspects will help you determine if the data is suitable for you to reuse and help you avoid investing effort and time in analysing data that is unsuitable.
Data Reuse. (n.d.). NNLM. Retrieved May 23, 2024, from https://www.nnlm.gov/guides/data-glossary/data-reuse
