Join us for the third session in the CaSDaR Data Stewardship Training series, dedicated to the FAIR principles. FAIR (Findable, Accessible, Interoperable, and Reusable) has become the cornerstone of open science and responsible data stewardship. This session will take you from the foundational concepts behind FAIR all the way through to practical implementation, giving you the tools and strategies to make research data and other research objects genuinely FAIR in your day-to-day work.

This training session will be run by Digital Curation Centre (DCC).

What You’ll Learn

By the end of this session, you will be able to:

• Explain the FAIR data principles and articulate their importance for research and open science
• Apply practical FAIRification approaches to datasets and other research objects
• Develop and evaluate metadata strategies that improve the discoverability and reusability of research outputs

Agenda:

• 12:30: Introduction to FAIR data and CARE principles
• 13:30: Assessing FAIRness of research data objects with F-UJI
• 14:30: Quality Assurance and FAIR Principles: Assessing and improving metadata quality for discoverability and reusability