• Inspirierende Role Models: Triff auf Frauen, die in der Tech-Branche erfolgreich sind. Sie teilen ihre persönlichen Geschichten und zeigen, dass der Weg in die IT viele Facetten hat.
• Spannende Einblicke: In einer interaktiven Panel-Diskussion beleuchten wir die vielfältigen Tätigkeitsfelder in der Informatik – weit über das reine Programmieren hinaus.
• Networking in lockerer Atmosphäre: Komm bei Häppchen und Getränken direkt mit den Expertinnen und anderen Studentinnen ins Gespräch, knüpfe wertvolle Kontakte und stelle all deine Fragen.

Prerequisites:

Prior knowledge about version control with Git is required. This can e.g. be acquired by attending the SSC’s introductory course “Version Control with Git” and “Intermediate Topics in Version Control with Git”. This course is intended for researchers that develop their own research software. Participants are required to bring their own laptops to work on during the course. Network access (e.g. through Eduroam) is recommended.

Summary:

Applying version control can be a game changer for a collaborative research software project. However, even in projects that already successfully use Git, there is often room for improvement of the employed Git workflows. This workshop explores some advanced topics that increase the participants’ repertoire of Git workflows: Bisection, Worktrees, Submodules, Large File Storage and Pre-commit Hooks. Additionally, we showcase invasive methods of modifying a Git repository via Rebase.

Learning Objectives:

After the course participants will

- Know about advanced Git features like submodules, large file storage
- Be able to bisect regression in a Git repository
- Understand the advantages of worktrees
- Be able to apply pre-commit hooks for their Git repositories
- Have used Rebase to change a repository’s Git history

Collecting, processing and analyzing data are central activities for virtually every researcher. Topics like data sharing and data publication are becoming increasingly important. Nevertheless, many research projects lack a structured and well-organized data management. This course is meant to give a general, discipline-independent introduction into various topics central to an efficient management of research data with a special focus on questions related to data archiving and data sharing. Both are central aspects of good scientific practice. Archiving and long-term preservation of research data are prerequisites for the scrutiny of scientific results based on the analysis of this data. Data sharing on the other hand increases transparency of research results and enables possible re-usage of data for new research questions, in combination with additional data sets and in interdisciplinary contexts.

In particular, the course will cover the following topics:
- Requirements on research data handling from universities, research funders and scientific journals
- Short-term and long-term preservation: formats, metadata, documentation, standards
- Open Research data, data publication and data citations: Where? How? Why and why not?
- Creation of data management plans for research projects