When developing your Research Data Management Plan, you will need to consider aligning activities relating to your research data with the University’s Data Retention Policy.
It is not possible to prescribe specific periods of retention, as all research projects will differ. However, MTU’s Research Data Retention Guide provides suggestions that should help you to plan your project and decide on what information you will need to retain and what to delete, with an emphasis on suggested schedules for data retention. It is your responsibility as the researcher to determine the appropriate steps for data retention.
You or your department may have specific needs that need to be considered when deciding on how to progress with your data, but in general, it is recommended to adhere to the principle of “as open as possible, as closed as necessary”, open to allow others to access your research, and closed to protect privacy.
Schedule of Data Retention
When drafting a research data management plan, and when planning for retaining data at the end of a research project, consideration should be given to how data is managed. In section 5b of the Science Europe recommendations for Data Management for example, sufficient criteria in a Research Management Plan (DMP) for data sharing and long-term preservation:
Provides details of what data collected or created in the project will be preserved in the long term and clearly indicates for how long. This should be in alignment with funder, institutional, or national policies and/or legislation, or community standards.1
In specific cases, these funder, institutional, national policies, community standards, and / or contract agreements will dictate what data is retained or deleted, but if not, then the data retention guide should be followed as per project needs.
Principles for Data Retention
The data to be collected should first be assessed for its value to you as the researcher and the broader research community and must be limited to what is directly relevant. This will determine if it will be useful and needed by other researchers in future.
The rationale for retaining data will depend on the research context. Ask yourself - what are the specific contexts surrounding the research? For example, clinical trials could last for up to 25 years, data on nutrition habits could last over 10 years, EU-funded Horizon projects could be aimed at re-using datasets only once and immediately, or Arts and Humanities data could involve musical performance videos that will have indefinite retention.
Reproducibility might be needed in the future for further research. This would be especially important in high profile / high impact studies, or studies that may later prove contentious. Longer term studies that may require a review in more than 20 years (life-long studies). Where studies have historical importance, they could potentially influence policymaking.
Further considerations that may be made on a case-by-case basis can be found on the Digital Curation Centre website, https://www.dcc.ac.uk/guidance/how-guides/five-steps-decide-what-data-keep
1 See: https://www.scienceeurope.org/media/nsxdyvqn/se_guidance_document_rdmps.pdf
