Data & Development Hub
Jupyter notebooks and RStudio environments for interactive analyses and calculations. Gitlab for project management and source code versioning
Development of Jupyter notebook
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JupyterHub - Python, R and Julia notebooks for data analysis
Jupyter logo
Graphic: Project Jupyter ContributorsWith JupyterHub, we offer an easily accessible option for Python, R and Julia notebooks. This environment enables interactive programming with fast feedback, enhanced by extensive documentation and visualisation options. Jupyter notebooks are ideal for rapid prototyping, interactive data analysis and visualisation, collaborative work, training courses, and for sharing ideas and descriptions of algorithms.
RStudio - Data analysis framework
RStudio logo
Graphic: RStudio, Inc.RStudioExternal link is the development environment for the statistics and data analysis-oriented programming language R. R is particularly suitable for analysing and visualising very large and complex data sets; many packages for a wide range of statistical methods are available in the R package repositoryExternal link.
GitLab - Code repositories
GitLab logo
Graphic: GitLab Inc.With the GitLab service, we offer you a central platform for the professional management of source code and the collaborative development of research software. The environment is based on Git and supports collaborative workflows, seamless version management and the implementation of open science standards directly on the university's infrastructure.
The range of functions goes far beyond pure code storage: integrated CI/CD pipelines enable the complete automation of test, build and deployment processes. A container registry (e.g. for Docker, Podman or Singularity) and package registries for various programming languages are also available for modern software workflows. GitLab also offers specialised functions for managing machine learning (ML) models and experiments for data-intensive research.