Introduction to Data Management Practices
Description
The Introduction to Data Management Practices course will cover key aspects of research data management through lectures, demonstrations, and hands-on computer exercises. This course is intended for researchers who want to take the first steps towards a more systematic and reproducible approach to documenting, describing and managing research data.
Topics covered will include:
- Open Science and FAIR in practice
- Organising data, files and folders in research projects
- Describing data with metadata
- Documentation using Markdown
- Publishing data to public data repositories
- Cleaning tabular data and metadata with OpenRefine
- Versioning data, documents and scripts (e.g. by using Git & GitHub)
- Writing Data Management Plans
What Participants Are Saying
"This course provided me with invaluable insights into managing my research data effectively!" - Participant Fall 2024
“Great course - should be made compulsory for as many students/PhD students/researchers as possible.” Participant Spring 2026
"The hands-on exercises were practical and easy to follow. Highly recommended!" - Participant Fall 2024
“This course should be mandatory for all new PhD students, and PIs too.” -Participant Spring 2025
“This course opens up a new world. A large world, like a maze. But the course provides some sort of map.” - Participant 2021
Content Providers
Learning Outcomes
At the end of the course, students will be able to:
- Describe some reasons for the principles of Open Science and FAIR
- Organise their project files and folders in a structured way
- Find and select relevant metadata standards for their research project
- Find suitable public repositories for life science data and have an understanding of the requirements for submitting data to them
- Clean up existing tabular data
- Perform basic version control of files and have means to learn more advanced skills
- Have an understanding of the benefits of data management plans (DMPs) and what a DMP should contain
Prerequisites & Technical Requirements
Prerequisites
No prior knowledge is required
Technical requirements
No prior programming experience is required, but you must bring your own laptop with the required software pre-installed.
Topics & Tags
Affiliations & Networks
Activity log
