As the @lmu_osc@scicomm.xyz coordinator, I was happy to give an overview of open research practices to students of the Bayerisches Zentrum für Krebsforschung. They were really engaged and while they didn't know about the replicability crisis, especially in cancer research, they already had implemented some of these state-of-the-art good reserch practices ! 🤩
In my presentation, I argued that to make your research the most credible and the most likely to replicate, you can engage with
1. preregistration, to increase the reliability of the research by reducing confirmation and hindsigth biases,
2. a finite set of computing tools (e.g. programing, version control, literate programing), to increase the reproducibility of your workflow.
3. FAIR data management to increase the quality and reusability of your data by being organised, documented, and standardised by design.
I also argued that researchers in medical field can still comply to FAIR data sharing by sharing their metadata openly on professional repository and set up a controlled access to their sensitive data, or only share anonymised or synthetic dataset..
Slides: https://osf.io/p9sev/files/t7br6
Our catalogue of self-paced tutorials to implement all this: https://lmu-osc.github.io/training/self-learning.html