Modern research with TRACE

Our Trusted Research Access & Cooperation Environment.

TRACE – Forschungsportal

IBE services

These services are part of TRACE - our Trusted Research Access & Cooperation Environment

IBE Cloud
IBE Cloud

Find your files. Share your files. Work together with tools in the IBE Cloud.

To IBE Cloud
Jupyter
Jupyter

Create models with R, Python or Julia. Test your model and share your code.

To Jupyter
RStudio
RStudio

Create models with R. Test your model and share your code with others.

To RStudio
IBE DokuWiki
IBE DokuWiki

Create documentation for your project. Extract to PDF files to share it.

To IBE DokuWiki
GitLab
GitLab

Versioning control for your code and sharing it with others.

To GitLab
LMU Zoom
LMU Zoom

Get directly to the official LMU Zoom login page (LMU username and password).

To LMU Zoom
REDCap
REDCap

For eCRF creation and web-surveys. Try the training environment.

More about REDCap
REDCap studies dashboard
REDCap studies dashboard

All IBE related REDCAp studies in one place. Filters can be applied.

More about REDCap

What is TRACE?

Trusted Research Access & Cooperation Environment

To Study Catalogue
Screenshot placeholder of TRACE Django platform

TRACE

TRACE is built with Django to provide a secure, auditable workflow for discovering studies, requesting access, and working in a Trusted Research Environment—without moving sensitive data.

The architecture integrates catalogue metadata, REDCap and CSV connectors, and sealed analysis spaces via Ginko, a qemu-web-desktop adaption. Role-based access control and detailed audit trails help teams collaborate confidently and stay compliant with institutional and GDPR requirements. By storing each researcher's variable selections alongside their access applications and the feature to save the corresponding analysis code, TRACE also enables the exact reproduction of analyses—even years later— ensuring transparency and long-term reproducibility.

From study catalogue to analysis

Researchers can browse rich study metadata, select variables, and submit access applications. Approved users work in remote desktops and notebooks connected to curated datasets.

Under the hood, Django orchestrates connectors, stores variable selections, and enforces Data Use Agreements (DUAs). Multiple data owners within an institute can register their own studies in TRACE and, when external researchers apply for access, establish DUAs that define the permitted use of the data. This keeps sensitive information under the control of its owners while still enabling reproducible workflows and efficient review.

Diagram placeholder for TRACE data access workflow