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Technical services for your data management

Services Computer Key
Photo: colourbox / #1728

Data_UMR (data repository for publication and storage of research data)
Electronic lab notebooks
Research Data Management Organiser (RDMO) (data management plans)
GitLab (versioning)
Hessenbox (Sync&Share)
JupyterHub (interactive Computing)
MaRC3a (high performance computing)
MaSC (high availability storage)
RedCap (structured data capturing)

data_UMR (repository for publication and preservation of research data)

data_UMR is a data repository for the publication and preservation of research data. It is a multidisciplinary repository that Philipps University maintains for those research data that do not or do not yet fit into a disciplinary repository. Your data will be kept in data_UMR for at least ten years. See the data_UMR website for more information.


The DataHub is a generic term for a set of tools that supports you, especially in 'active data management', in the traceable processing and analysis of data. Contact for more information

Electronic lab notebooks

We are currently establishing joint services for electronic lab notebooks in the HeFDI network. Until the end of 2024, these are exclusively test operations. In principle, there is therefore the possibility to test services such as eLabFTW and Chemotion. If you are interested, please contact .

Research Data Management Organiser (RDMO) (Data Management Plans).

The RDMO is a tool that allows you to create a data management plan. More information.

GitLab (Versioning)

GitLab version management is provided centrally as a service by Philipps-Universität Marburg. Based on the distributed version management tool Git, it enables versioned storage and management of data and is ideal for software development and working on research data (active data management). Especially in collaborative work, GitLab can generate added value for any team. This is because GitLab also supports working in groups and in projects, e.g. through project-specific wikis, issue tracking (ticketing systems) or Kanban boards. In addition, GitLab offers tools for quality assurance of code and data (Continuous Integration). The appealing presentation of projects and their results is also directly possible via GitLab Pages. More Information

Hessenbox (Sync&Share)

Hessenbox is available as a cloud solution for sharing data and datasets (no sensitive data).

JupyterHub (Interactive Computing)

JupyterHub is provided centrally as a service by Philipps-Universität Marburg. It enables the web-based use of JupyterLab and thus in particular also interactive coding, interactive computing as well as the interactive processing, analysis, visualization and output of research data. The computations are performed on different platforms depending on the application scenario; for research currently on the MaRC3 high-performance computing platform designed in Marburg for high-performance computing. More information.

MaRC3a (High Performance Computing)

In addition to a wide range of software and licenses, the HRZ also provides resources for High Performance Computing (HPC). In order to not only meet current requirements, but also to provide the best possible support for cutting-edge research in the field of BigData and AI, MaRC3a/b is ready. Preparations for MaRC3c (MaRCQuant) with a focus on quantum physics computations are already underway. The computing clusters are available to all researchers of the Philipps-Universität free of charge. If you have a need for the computing services, please contact the High Performance Computing team of the HRZ.

MaSC (High Availability Storage)

High-performance computing is complemented by a compute-oriented, high-availability storage cluster, known as MaSC, which enables the efficient handling of big data. In addition to storage for the purpose of processing big data, MaSC is also explicitly available as "hot" and "cold" storage for Philipps University working groups. For example, imaging and omics data can be stored there directly from the measurement devices. By sharing the storage cluster, the available capacities can be optimally utilized. There is no need to maintain individual storage systems for individual workgroups. For all questions about the storage and HPC cluster, please contact

RedCap (structured data capturing)

Do you want to record your digital data for surveys or other research processes in a comprehensible, structured and secure way? For this purpose, UMR, in cooperation with KKS, provides a simple and intuitive system for data collection: RedCap . The tool can be used for all projects that are NOT subject to a regulated environment, e.g. according to ICH-GCP, AMG or MPG. More information