The Galaxy Training Network: A Powerful Framework for Teaching Science
DescriptionDespite the ongoing explosion of scientific datasets being generated, brought on by recent technological advances in many scientific areas, basic computational skills, data analysis, and stewardship are still rarely taught in educational programs. In order to address this skills gap and empower researchers to perform their own data analyses, the Galaxy Training Network (GTN, has put together a collection of FAIR (Findable, Accessible, Interoperable, Reusable) training materials for data analysis utilizing the user-friendly Galaxy framework as its primary data analysis platform. The number of tutorials and contributors is growing rapidly. The topics now range from life sciences to climatology, cheminformatics, and machine learning. While initially aimed at supporting researchers directly, the GTN has proven to be an invaluable resource for educators as well. Recent efforts have focused on adding increased support for this growing community of instructors. New features have been added to facilitate the use of the materials in a classroom setting, simplifying the contribution flow for new materials, and have added a set of train-the-trainer lessons. I will present a general overview, describe the available infrastructure and discuss the latest developments in the GTN project.
TimeTuesday, June 2712:00 - 12:30 CEST
LocationSanada II
Event Type
Computer Science, Machine Learning, and Applied Mathematics