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The Data Lifecycle

What is the data lifecycle?

Data often have a longer lifespan than the research project that creates them. Researchers may continue to work on data after funding has ceased, follow-up projects may analyse or add to the data, and data may be re-used by other researchers. The data lifecycle captures this in its representation of 3 phases:

 

Planning & Preparation Phase

  • Determine what data you will generate
  • Identify data storage and security needs
  • Write your data management plan

 

 

 

 

 

 

Active Research & Data Gathering Phase

  • Actively create and securely store research data
  • Conduct data analysis and evaluation
  • Where applicable, share data with co-researchers

 

 

 

 

 

 

Post-Research Data Storage and Access Phase

  • Migrate data to optimal format for long-term use
  • Distill large research dataset to that supporting your research conclusions
  • Document your data (how it was created, when, for what project, etc.)
  • Archive data in appropriate repository for long-term storage
  • Share and promote data

 

 

 

 

 

 

 

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