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Knowledge sharing in academia has been considered indispensable and is becoming a priority in most European funding schemes. Although we are already quite familiar with the different possibilities to publish our results in open-access journals, open science means way more than that. Open science aims at opening up research processes and granting access to research outputs to researchers, professionals and amateur scientists. There are different ways to ensure the storage and reusability of our data, making it available to other scientists. Furthermore, most of the scientific disciplines migrate their analyses to open-source environments (e.g., R, Phyton). However, tons of code produced remain stored in our personal computers either because we do not know the appropriate tools to share them with our colleagues or because we believe that it is not well structured.
In this short course, you would learn how to establish links between publications, data, software and methods. Hence, we will discuss with our experts: i) the options to share our data and code with other peers, ii) obtain some tips to better organize our scripts, and iii) uncover potential barriers to sharing research and discuss possible solutions.