Module: FAIR Data Management, Security and Ethics

Learning Outcomes

You understand and can apply FAIR data management practices


HI-DSI Code of Conduct

We are dedicated to providing a welcoming and supportive environment for all people, regardless of background or identity.

Hydroshare Setup

Setup account for Hydroshare website

Experiential Learning

1. Introduction

Who are we and what are we going to learn?

2. Open Science

What is Open Science? How can I benefit from Open Science? Why has Open Science become a hot topic?

3. Intellectual Property, Licensing, and Openness

What is intellectual property? Why should I consider IP in Open Science?

4. FAIR Introduction

What are the FAIR principles? Why should I care to be FAIR? How do I get started?

5. Fair: Findable

What is a persistent identifier or PID? What types of PIDs are there?

6. FAIR: Accessible

What is a protocol? What types of protocol are FAIR?

7. FAIR: Interoperable

What does interoperability mean? What is a controlled vocabulary, a metadata schema and linked data? How do I describe data so that humans and computers can understand?

8. FAIR: Reusable

What makes data reusable?

9. Metadata

What is metadata? What do we use metadata for?

10. Public repositories

Where can I deposit datasets? What are general data repositories? How to find a repository?

11. Exercises

What makes this dataset FAIR?

12. Ethics

What ethical considerations are there when making data public?

13. Security

What measures will you take to secure your data?


Help us assess this workshop

Provide feedback to the workshop organizers

Outcome(s) assessed: You understand and can apply FAIR data management practices