Research Data Lifecycle

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Research data lifecycle

Good research data management practice runs throughout a project and continues after a project has finished. 

There are several stages in the research data lifecycle, as shown below.

RDLifecycle208x110
 

Grant proposal planning and writing

  • generation of ideas and examining existing datasets
  • discovering what data services are available from the University
  • scoping the project outputs and the type of data that will be produced
  • considering the options and costs for data storage or archive requirements
  • clarifying any licencing requirements
  • working with colleagues to identify who else could benefit from the data
  • understanding funding requirements for data sharing & archiving
  • creating a data management plan

Publication of the data or an article

  • check the funding requirements regarding publishing the data that underpins an article
  • deposit data in either the University data archive, in a subject repository or publisher repository
  • include the data citation in the paper
  • include details of the publication in the end of project report

Archive and preserve data

  • submit data sets to either the University data archive or to a subject repository
  • record where the datasets are and a citation that links to them in the end of project report
  • share your work with collaborators and subject experts to encourage data reuse

Project start and award stage

  • clarifying collaborative agreements and any licencing issues
  • request the data infrastructure to store the working data

During the research

  • organise, manage and document the data and create metadata to describe what is being produced
  • keep to good practice around file naming and versions of the data
  • ensure your research data is safe from uncontrolled access or accidental loss by using secure and backed-up storage media
  • take snapshots and archive data that is significant
  • share data with collaborators or publicly if required
  • conduct audits and delete or archive data that is no longer relevant or has been superseded 
  • check your file formats are OK and migrate any that will become obsolete
  • document any specialist software, equipment or parameters that will be needed to reuse or view your data