📢 Learn how data can be managed to facilitate the discovery and reuse of data, for humans and machines.(2016, FAIR Guiding Principles for data management and stewardship). 📢
Digitalisation has had a considerable impact on the way we work in everyday life. What is more, this technological advancement has also resulted in a substantial increase of research data being produced worldwide. Research data transforms the way we live and work, so it’s becoming increasingly important that it’s stored and organized correctly. In parallel, the number of personas involved in a project are more diverse than ever - researchers, data stewards, librarians, data scientists and software developers - with all different digital skills. Therefore, the concept of FAIR data management is currently a topic of interest within and beyond academia, with universities being increasingly aware of the need to provide trainings on data-driven methods for doctoral candidates , early-career researchers and data stewards. This interactive, online workshop will provide a platform to address the importance of FAIR data management practices for them and explore practicalities to make your research data FAIR.
You’ll discover common research data management techniques, how to create FAIR data in practice, and how to develop your own research data management FAIR roadmap. By the end of this workshop you will be able to:
- ✔️ Demonstrate the concept of FAIR and its applications in research data management.
- ✔️✔️ Articulate benefits, barriers and challenges in making data and other outputs FAIR.
- ✔️✔️✔️ Gain hands-on experience with techniques, services and technologies to make your data or help other make their data FAIR.
This course is aimed at individuals working with or expecting to work with research data as researchers, librarians, data stewards, and all of those aiming or determine to make their data FAIR.
First round: 10th February 2021
🧭Next round: Stay tuned
| Time | Topic | Duration |
|---|---|---|
| 10:00 | S1: Welcome to the workshop and Introductions | [15min] |
| 10:15 | S2: The why, what and how of FAIR | [1hr] |
| 11:15 | Join: FAIR Quiz I | [15min] |
| 11:30 | Coffee break | [15 min] |
| 11:45 | S3: Introduction to FAIR Activities | [15min] |
| 12:00 | Hands on Session | [1hr] |
| 13:00 | Lunch break | [1hr] |
| 14:00 | Discussion Q&A FAIR experience | [15min] |
| 14:15 | S4: Evaluating FAIRness | [30min] |
| 14:45 | FAIR Quiz II | [15min] |
| 15:00 | S5: The road to the next Science | [15min] |
| 15:15 | S6: Wrap up, next steps and Workshop Evaluation | [15 min] |
| 15:30 | end |
- Introduction
- FAIR Concept
- Challenge 15 principles in 25 min
- UM Repositories
- FAIRness Evaluation
- Next Science
Please provide us with your feedback, so we can continue to improve our workshops.
The Slack workspace will be used to keep open for a further two weeks after the end of the course.
All bodies involved in the Community for Data-Driven Insights:
