You understand and can apply FAIR data management practices
You understand basic FAIR (Findable, Accessible, Interoperable, Reusable) concepts.
You recognize that engaging in data management early can help you and others understand your project.
You recognize the barriers and risks in the adoption of Open Science practices.
You understand intellectual property, licensing, and openness.
You understand the components that uniquely identifies a research publication.
You have learned how to identify a FAIR dataset.
You understand what metadata is and how to distinguish between different types of metadata.
You understand privacy, freedom, explainability, and fairness as they go into managing data ethics.
You have (potentially) identified useful changes to your current habits regarding data management.
Readings
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?
Assessments
Help us assess this workshop
Provide feedback to the workshop organizers
Outcome(s) assessed:
You understand and can apply FAIR data management practices