Research data at the TU Darmstadt

Welcome to the TU Darmstadt website on handling digital research data. Here you will find all the basic information, our services and also contact persons for further questions.

Digital Research Data at TU Darmstadt

Welcome to the web pages of the TU Darmstadt for dealing with digital research data!

The TUdata team, which was formed in 2018, supports all members of the university on behalf of the Executive Board in securing, archiving, publishing and re-using research data. To this end, the University and State Library, the University IT Service and Computing Centre and the Department VI – Research and Transfer work together at TUdata.

In December 2015, the university adopted guidelines on digital research data at the TU Darmstadt.

Our topics and services

Research data management , e.g. with the TU-GitLab and the Hessenbox

Retrieval and citation of research data

Creating data management plans using the TU data management organizer TUdmo

Archiving and publication of research data with TUdatalib

What are Research Data?

Research Data are the most essential resource in modern science. Scientific hypotheses and theories are formed and verified by research data. The German Research Foundation (DFG) considers their Guidelines on how to deal with Research Data from 2015 as “crucial foundation for all scientific work”. The DFG also points out the importance of research data for research and science by acknowledging that the variety of research data “resembles the variety of scientific disciplines, epistemological interests and research types.”

The Guidelines on digital research data at TU Darmstadt define research data as all digital data, “that are produced during the process or as the outcome of experiments, measurements, simulations, software developments, studies of primary sources, inquiries or surveys.” This includes everything from pictures to multi-dimensional models, audio and video recordings, texts, tables, databases and even computer programs (source code and application software). Subject or device specific raw data in various formats are also considered as research data.

To make use and understand research data, correct documentation and software is vital. Research data are often preserved in different aggregation levels and very specific digital formats that correspond to their different disciplines.

FDM in third-party funding applications

Depending on the funding organisation, there are different requirements for research data management. The costs incurred for corresponding measures, e.g. to increase reusability, can partly be claimed in the context of applications.

The DFG summarises all information on the page Handling Research Data. It provides a checklist that should be consulted when submitting an application. Depending on the funding programme, there is also additional information. If costs are incurred in order to make data reusable and accessible, these can be applied for.

The Horizon Europe programme is based on the paradigm of Open Science. The credo for research data is “as open as possible – as closed as necessary”. This means that the goal is primarily to make the resulting research data available as open data, although this can be waived in justified cases.

The creation of a data management plan is obligatory as a deliverable within the project after six months at the latest. A template is provided for this purpose, which is primarily aimed at the FAIR principles. In addition, however, the handling of research data must also be described in the application.

Further information:

Horizon Europe Programme Guide (opens in new tab)

Horizon Europe Data Management Plan Template

The BMBF does not make any general specifications for research data management. Depending on the funding programme, there are few or very high requirements for data management. With the Research Data Action Plan, the BMBF also supports projects on data-related research, standardisation and the teaching of data skills.

Research Data Action Plan

Subject-specific aspects

Many aspects of research data management are determined by subject-specific factors. This applies in particular to the way in which data are obtained, the object of study and the nature of the resulting data. Accordingly, the appropriate approaches and the tools that support them are also dependent on the respective discipline, as are suitable metadata standards or terminologies for describing and documenting the research data.

Recommendations for approaches and suitable tools and standards are being developed in Germany for many disciplines within the framework of the National Research Data Infrastructure (NFDI). An overview of the active NFDI consortia can be found here:

The NFDI consortia are a good point of contact for discipline-specific research data management issues. If required, we will be happy to identify a suitable contact for you.

If you want to make your research data citable and re-usable through publication, there are specialised subject repositories for many disciplines and data types that make the research data stored there searchable on the basis of subject-specific parameters and visible to a specialist audience. You can search for suitable repositories via