Research Data Management and the Data Life Cycle

Most data disasters are decided before collection even starts. This level builds the mindset and the plan behind trustworthy data: what research data management is, the six stages of the data life cycle, and how to write a Data Management Plan that funders and journals now expect.

Who this level is for

Data managers, data officers, coordinators and principal investigators, and anyone responsible for study data, across low- and middle-income countries. No technical background required.

What you'll learn

• Why good data management saves time and protects your findings, and what poor management costs
• What research data management is, and who owns it (investigators, data managers, IT, statisticians)
• The benefits for you and for open science: less cleaning, more analysis, and data others can reuse
• The six stages of the data life cycle: plan, collect, assure, describe, preserve, analyse
• What a Data Management Plan is, what it must decide upfront, and why it is a living document
• How to translate your study procedures into a clear data-flow diagram

You finish with: A one-page Data Management Plan sketch + a data-flow diagram.