Research Data Lifecycle

A model to conceptualise the different stages through which data pass during the research process, and the data management activities that relate to those stages.

The model used throughout Data Tree has six stages, corresponding to different activities during the life of a research project. Other institutions or paradigms have slight variations on these stages, but the broad concepts are applicable no matter how you choose to categorise your research activities. 

Our model is based on the UK Data Service model from 2011, and has the following stages: 

  • Re-using Data: Often considered both the start and the end of the cycle. Your research might start by gathering secondary data, and your own research outputs might be later used by yourself or others in different sectors.
  • Creating Data: Data collection or generation activities.
  • Processing Data: The tasks of turning raw data into analysis-ready data. This includes quality control checks, data cleaning and documentation.
  • Analysing Data: Includes data visualisations and statistical analysis; tasks that involve the process of getting information out of your data.
  • Preserving Data: The tasks of putting your data into a location for long-term storage and access, such as a data repository.
  • Making Data Accessible: This includes not just ensuring your data can be accessed, but also making others aware of your data. This might include publishing in a data journal and adding appropriate licences to your preserved data.

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