Data and the FAIR Principles

FAIR is a collection of guiding principles to make data Findable, Accessible, Interoperable, and Re-usable. This module provides a number of lessons to ensure that a researcher’s data is properly managed and published to ensure it enables reproducible research.

It is based on the lesson template used in Neurohackweek, Data Carpentry and Software Carpentry workshops.


09:00 Module Overview: Data and the FAIR Principles Why is FAIR important?
Who is this module for?
How can I get some help if I get stuck solving an exercise or answering a question?
When and where are the future ReproNim training workshops?
09:00 Lesson 1: Introduction to the Web of Data What is a research object and how do I properly identify it?
What is linked open data?
What are the FAIR Data principles?
09:02 Lesson 2: Ethics What ethics policies and issues surround privacy, data sharing, and the use of data?
09:02 Lesson 3: Data Publishing Am I ready to publish my data?
What resources are available for your research data needs?
09:03 Lesson 4: Your Laboratory Datastore What resources are available for me to be a good steward of my laboratory’s data
09:03 Lesson 5: Semantic Data Representations How do I represent my data as linked data?
09:03 Finish