TUM Research Data Hub

The TUM Research Data Hub is the central point of contact for TUM researchers and partners in all matters of research data management (RDM), following the TUM guidelines for handling research data. Our service portfolio includes consulting, training, networking events, infrastructure solutions, tools, and handouts for all phases of a research cycle.

The goal of the cooperation between the Research Data Services of the University Library and the Munich Data Science Institute (MDSI) is to offer practical, high-quality solutions for sustainable RDM to the TUM community.

Abbildung zeigt ein Zoom-Meeting

Zoom – Migration to Telekom tenant

TUM has extended its contract with Zoom for another year, switching to the new contract partner Telekom.

Appointment portal online

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Appointments to new professorships can now be managed and advertised via TUM’s new appointment portal.

Digital statutes and regulations

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Statutes can now be published purely digitally due to a legal amendment in the Higher Education Innovation Act (HIG).

Travel management with BayRMS

Since January 2023, BayRMS has been available as a digital system for requesting and billing short domestic trips.

Vulnerability scans on all IT systems

Our IT security team has started to scan all of TUM networks for security vulnerabilities within our systems using the Greenbone Security Assitant.
die Abbildung zeigt einen Screenshot des TUM Roomfinders

New TUM Roomfinder

The new Roomfinder is available at https://nav.tum.de and replaces the previous, very outdated Roomfinder.

Koinon IT Portals available for all schools

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Koinon (from ancient Greek community, commonwealth, or federation) is a portal for the digitalization of administrative processes at schools.

Generate your user certificate on your own

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As a student or employee/guest of TUM, you can easily generate a user certificate for your TUM email address(es) via TUMonline.

Data science storage available to all scientists

LRZ’s Data Science Storage (DSS) is a novel approach at LRZ to solve the demands and requirements of data-intensive science.