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Goals ----- This course introduces core Open Science aspects, like Open Data and Open Access, and key practices to make research more open, trustworthy and reproducible. It covers the entire “lifecycle” of a research project from the considerations that need to be taken before running an experiment to data analysis and finally dissemination. Learning outcome ----- Participants in this course will have a good understanding of basic Open Science principles. They will learn the advantages of open research for themselves and the research community as well as some of the challenges they might face. Participants will also gain some practical skills, like using the Open Science Framework and different R packages to make their research more reproducible. Participants will end the course feeling like they can apply a range of Open Science tools to their own research. Instructors (including Guests) ----- - Eirini Zormpa - Julia Egger - Greta Kaufeld (Session 0) - Guillermo Montero-Melis (Session 2) - Andrew Jessop (Session 4) - Phillip Alday (Session 5) Syllabus ----- You can find the syllabus [here](
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Free and easy to use, the Open Science Framework supports the entire research lifecycle: planning, execution, reporting, archiving, and discovery.