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Research Data Management

Reusing & destructing data: Determine your research data retention policy

Data retention defines the policies of persistent data and records management to meet archival requirements.  As a researcher it is pivotal to prepare a detailed data retention policy as part of your DMP, to define why and how you store your research data, for how long, how you dispose of it and which might be used at a later stage.  

There is a number of considerations which influence and determine retention periods for research data and include:

  • The purpose of retaining data - is retention necessary for research purposes and/or necessary to secondary users?
  • Funding body requirements - how long does the research funder require the data to be stored for and how does this matches the retention purpose?
  • The type of the research data - are they sensitive data or data that might affect the participants?
  • Nature of research under review - does the field require retention of data for the continuity of scientific research (i.e. historical or statistical research data)
  • Legislative or regulatory requirements - for example, statutory retention periods for medical research
  • University and/or institutional policies on data management
  • Agreements with research and industry partners in case of a collaborative research project

Some research data may have have research value for researchers and the general public that require to be kept for a much longer period or even permanently.  A carefully prepared data storage policy for subsequent use prevents researchers from collecting repeatedly the same data and protects participants from inefficient research practices.

 

Research data disposal and reuse

Research data disposal and reuse ensure the quality, integrity, and accessibility of research data, and accelerate scientific progress.

Your research data disposal should be completed once the retention period has passed and you feel that the data is no longer of value and they follow the requirements included in the retention policy.  Data files destruction is a critical component of managing data securely and it can be applied at different stages in the data cycle, taking under consideration that different material types require different destruction/disposal methods.

Failure to properly destroy the data can lead to serious breaches of data-protection and privacy policies, compliance problems and added costs. There are three main options for data destruction: 1) Overwriting, 2) Degaussing, and 3) Physical Destruction. 

You overwrite data when you write new data on top of old, erasing the old material and leaving everything completely unreadable.  On the downside, it takes a long time to overwrite an entire high-capacity drive.

Degaussing refers to the process applied to magnetic storage media (i.e. hard disks), to disrupt the magnetic field of the storage medium and destroy the data.

Physical destruction is a possible and common data destruction option for hard drives.  Nevertheless, due to human error, there is no reliable way to audit the process with large portions of the drive being left intact, even if the drive is inoperable.

The best method of data destruction depends upon the type of media, the sensitivity of the data, and the end-of-life value of the assets.

"Data reuse means using data for other purposes than it was originally collected for. Reuse of data is particularly important in science, as it allows different researchers to analyse and publish findings based on the same data independently of one another. Reusability is one key component of the FAIR principles.  Data that is well-described, curated and shared under clear terms and conditions is more likely to be reused. Integration with other data sources is also important, since that can enable new, yet unanticipated, uses for the data." [RDM Kit] 

Before starting off with your research project, check whether the data you need already exist.  Over the years, there has been an exponential increase in the volume of data generated for research purposes.  These, can be found stored in repositories and other sources and might be applicable to your own research.  Therefore, consider reusing existing data, rather than producing new research data yourself.

The benefts of reusing research data:

  • It maintains research continuity
  • It saves time and resources
  • It’s a way to find new collaborators and foster interdisciplinarity
  • It boosts research visibility
  • It exposes data to new tools, methods, and approaches
  • It contributes to the scholarly community and society at large

Citing the data in your publications is is a pivotal aspect of data sharing.  Additionally to this, acknowledging the work of others ensures research integrity. Make sure to always cite any research data you reuse.

-> The Oregon Health and Science University (OHSU) has compiled a list of various sources where you can discover research data.

-> Likewise, you can find many data repositories and other sources from the University of Wisconsin - Madison.