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.
|09:00||Module Overview: Data and the FAIR Principles||
Why is FAIR important?
Who is this modulde for?
How can I get some help if I get stuck on solving for an exercise or 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 Labortory 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?|