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