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Research Data Management: Sharing & Archiving

Sharing and Archiving: What do we mean?

The term 'sharing' data is used in different contexts.  It may mean sharing data within your project team during the life of the project.  However, the term is often used to mean sharing your data with the wider research community or the public.  It's important to be clear about which kind of sharing you are referring to when writing data management plans.

'Open Datais one form of data sharing.  This normally refers to making data publicly available, downloadable and re-usable through a data repository such as DMU Figshare or a subject-specific repository like the UK Data Archive. 

 

'Archiving' data means storing data for the long term.  This might be either with or without public access to the data.

Deciding what to do with your data

During, and especially towards the end of your project, you will need to make decisions about what will happen to your data after your research project is completed.  Some of the elements you will need to consider are:

  • Funder expectations
  • Ethical and data protection considerations
  • Which data may be useful to the wider research community
  • Which data would be needed to reproduce your research
  • Which data can be made publicly available
  • Which data can be archived but not made publicly available
  • Which data can be deleted.

This process is known as data appraisal.  You will have thought this through at a high level when producing your data management plan.  However, you will need to carry out a detailed appraisal towards the end of the project.  It is worth factoring in time and cost for carrying out this activity in your project plan and bid.

How to appraise and select research data is a useful guide from the Digital Curation Centre.

DMU RDM Guidance

DMU will shortly be putting in place a new Research Data Management Policy.  In the meantime, please refer to the 'Good Practice in Research Data Management' Guidance.

DMU RDM Training

 

Click to go yo the DMU Research Data Management Course