Reproducible research is a concept that has become of great interest in the last years, spanning all disciplines of science, from STEM to humanities. In a nutshell, the core question that this concept relates to is: "can the results of a study be independently reproduced by a separate entity?". While simple in a formulation, this question encompasses a multitude of ancillary problems, namely: ● Does the published research contain all the elements needed for the reproduction of the results? (i.e. will other researchers obtain the same results from the same data?) - Is the research accessible at all? (Open Access) - Are the methods self-contained or do they rely on a closed implementation? (Open Source) - Are the data available for independent analysis? (Open Data) ● Do the results reflect a correct view of the world? (i.e. will other researchers observing the same population/phenomenon reach the same conclusions?) - Was the study correctly designed in the beginning? - Did it have enough statistical power? - Were the methods adequate (repeatable, reproducible)? - Was there any publication bias? In this course, we will discuss the aforementioned issues together with invited speakers and under the light of selected literature. This course primarily targeted to PhD students, but also open to Master students and all interested researchers. It is crucial that all researchers, and especially the ones at the beginning of their academic careers, have a knowledge of these questions and of the current tools that the scientific community is using to provide answers to them. Course Home Page: https://dbe.unibas.ch/en/education/doctoral-studies/open-science/