Huge efforts are made to develop powerful computational modeling and data analytics tools for the Geosciences. This quite naturally results in a (sometimes overwhelmingly) large amount of digital techniques for both computational model development as well as research data life-cycle management.
This seminar offers a platform to introduce and discuss selected digital techniques of relevance to geoscientific workflows, e.g. code prototyping with jupyter, version control with gitlab, cross-platform collaboration with docker, or a review of some useful software libraries. This semester's focus will be on how to deal with different types of data acquired in geoscientific research using python and jupyter notebook, and research data management.
After a series of (virtual) overview lectures, the students will have the opportunity to deep-dive into one of these techniques, while working on predefined seminar projects. These projects are inspired by applications in cryosphere physics and natural hazards research, yet their clear focus is on an investigation of the (transferrable) digital techniques. The students can work alone, or preferably in small teams (two or three). Progress will be discussed in regular (virtual or in-person) meetings. The project's results will be presented and discussed in the group (either virtually or in-person)