Data Management
FAIR TRAINING
Data Management
FAIR TRAINING
What are FAIR Principles?
FAIR principles are a set of guidelines for making research data Findable, Accessible, Interoperable, and Reusable. These principles aim to increase the value and impact of research by promoting good data management practices that enable data to be effectively shared, discovered, and reused by both humans and machines.
Learning Goals
- 1
You will get acquainted with the principle of integrity and reproducibility by design.
- 2
You will be able to identify the elements which should be present in a data management plan (DMP).
- 3
You will get acquainted with preregistration as a tool to increase integrity and reproducibility.
Reading Material
FAIR and Data Management
Videos
What is FAIR? - and why should you be interested in it?
How do you make your data interoperable? - and why is it important?
How do you publish your research output? 5 points
What is good data management? - and what is the value of it?
How do you write good data-handling practices into your applications?
E-Learning
Tools
Policies
Research guidelines
Talk to CLAAUDIA
CLAAUDIA is a specialized team of data scientists, data managers and data stewards within ITS who provide access and support for a line of virtual services to researchers as well as assistance in data management planning, active data handling, data publishing and data archiving.