Do you know that feeling, when you work on your research project after not having looked at it for a while (for example after receiving reviews) and you can’t remember how the different parts fit together?
And when you finally figure it out again, the results are somehow different. Oh no!
In this course we will set you up to never run into these kinds of issues again.
Let’s get your research project organized, under version control, stable, and published so that you can confidently say that your research is reproducible.
Topics
- The goal of producing FAIR and reproducible research outputs
- Working on research projects as a team
- Get your project organized: organized folders, naming, documentation
- Set up reproducible workflows: version control with git, stable computing environments, and automation
- Make your project reproducible and FAIR for all: publication platforms, licensing, and more
Format
This is an online course. Each week you will:
- watch the 📺weekly videos (~45 min),
- review one of the 📖 booklet chapters,
- have a short session with your 👤 accountability buddy* (15-20 minutes),
- implement the ✍️ tasks of the week, and
- discuss your progress in the 👩🏫 weekly online meeting with the instructor and fellow course participants (1-1.5 hours).
* You will choose your accountability buddy during the course. You and your buddy will help each other in implementing the tasks of each week.
Weekly Meetings
The course includes 5 Online Meetings, in which you will discuss the week’s contents with the instructor and fellow participants:
Meeting 1: Sep 25, 3:00 – 4:30 pm CEST
Meeting 2: Oct 02, 3:00 – 4:30 pm CEST
Meeting 3: Oct 09, 3:00 – 4:30 pm CEST
Meeting 4: Oct 16, 3:00 – 4:30 pm CEST
Meeting 5: Oct 23, 3:00 – 4:30 pm CEST
Prerequisites
- Basic programming knowledge (R, python, …)
- Willingness to learn new technical skills
About the Instructor
Heidi Seibold holds a PhD in Biostatistics with a focus on Machine Learning. Her research has been in the intersection of Data Science, Reproducibility and Medicine. She is a solopreneur in Open and Reproducible Research and an independent researcher at IGDORE. Heidi is the co-founder of the Digital Research Academy and Open Science Freelancers.