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University of Cologne

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University of Cologne

Faculty of Medicine

Institute for Biomedical Informatics

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Susanne Vorhagen

Susanne Vorhagen (Dr. rer. nat.)

Project Coordinator/ Data Steward

ORCID: 0009-0005-0822-3107

Biography

Susanne Vorhagen studied Biology at the University of Cologne. During her PhD at the University Hospital Cologne, she combined fundamental science with clinically-relevant research questions in the field of skin cancer. After qualifying as a project manager, she worked as a medical advisor in healthcare communication and scientific coordinator of collaborative DFG-funded research projects. As member of the MeDIC team, Susanne is responsible for the development of advanced solutions for research data management challenges in the field of biomedicine.

Contact

Email susanne.vorhagen@uk-koeln.de
Phone +49 (0)221 478-84811
Office MeDIC - Geb. 5 -Gleuler Str. 70 - 50937 Köln - 2 OG - Room 2.007
https://www.linkedin.com

Academic Background

Areas of Expertise

Tools & Services

Hospital External Data Delivery via Medical Data Integration Center (MeDIC) and FDPG

A central task of the MeDIC is the provision of medical care data for authorized external people.

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Symbolic Image - Research Data Management

Consulting and Training in Research Data Management

This service brings together expert consulting and focused training to support good research data management in practice. Researchers receive tailored advice for their specific projects, alongside hands-on training that develops skills in data planning, documentation, storage, and reuse. The aim is to promote reproducibility, improve data quality, and support compliance with funder, institutional, and ethical requirements.

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FAIRdata Cologne

FAIRdata Cologne is a Dataverse-based metadata catalogue for documenting and discovering experimental research activities. It supports collaboration within projects such as CRCs and, where desired, increases the visibility of laboratory research to the wider scientific community.

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FAIRspace Cologne

FAIRspace Cologne is a GitHub-based platform offering practical guidance, tools, and community resources to support FAIR and effective research data management.

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Research Electronic Data Capture (REDCap)

REDCap is a secure web application for electronic data capture, created in 2004 at Vanderbilt University. It allows researchers to develop customized data collection instruments (online surveys), single or multi-site data collection and management of the research database.

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Research Projects

CRC 1607

The goal of this central INF project is to provide software and hardware infrastructure and methodology for storage, management, retrieval and analysis of the data generated within the CRC 1607, with particular focus on images. Almost every project in this consortium will generate imaging data and will also be linked to the central project Z02. [...]

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ARTICYST

Prediction of clinically relevant outcomes is a key asset in chronic non-communicable diseases to guide both patient counselling and targeted therapeutic strategies, and can be a catalyst to demonstrate the impact of Open Science practices when appropriately deployed. [...]

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Restore Vision

Restore Vision is a collaborative European research project dedicated to developing and testing new treatments for seven rare eye diseases (REDs) that affect the cornea and ocular surface. These diseases are a significant cause of visual impairment and blindness across all ages, yet current treatments are often expensive, ineffective, and come with serious side effects. [...]

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FAIR4Rare

There are more than 6,000 diseases, each of which is extremely rare. In total, however, several million people are affected in Germany alone. A disease is considered “rare” if it affects no more than five in 10,000 people. The National Register for Rare Diseases (NARSE) serves to record as many affected people as possible in the long term in order to determine the health effects and care structures of these diseases in Germany. [...]

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CRC TRR 422 PodoSigN

TRR 422 is a Collaborative Research Center funded by the German Research Foundation (DFG) at the Universities of Cologne, Münster and Hamburg. In this network, researchers are investigating the molecular control processes of structurally complex kidney cells known as podocytes. [...]

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GNAO1-EU

GNAO1-associated disorders encompass a wide spectrum of neurological disorders featuring variable association with early-onset movement disorder, epilepsy, developmental delay and intellectual disability. GNAO1-associated disorder is an ultra-rare disease with an unknown prevalence. [...]

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NUM DIZ 3.0

The NUM-DIZ project of the Network of University Medicine (NUM) builds on the preliminary work of the Medical Informatics Initiative (MII), within which Data Integration Centres (DIZ) have been established at most German academic medical centers with the aim of supporting data provision and cross-site data integration and analysis. [...]

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Focus Areas

Data Integration, Interoperability & Standards

High-quality medical AI depends on data that is not only accurate, but also consistent, connected, and usable across systems. Therefore, we focus on integrating heterogeneous data sources, ensuring interoperability, and advancing the use of open standards. By harmonizing clinical information from clinical records we enable reliable analytics, reproducible research, and scalable AI solutions. This work lays the foundation for transforming fragmented healthcare data into meaningful insights that support better decision-making, improved patient outcomes, and more efficient workflows.

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Research Groups

Research Data Management

Susanne Vorhagen

At the Institute for Biomedical Informatics, our Research Data Management (RDM) team plays a key role in enabling the effective, sustainable, and FAIR (Findable, Accessible, Interoperable, Reusable) handling of medical and biomedical research data. We work closely with researchers, clinicians, and data stewards to ensure that data is collected, documented, and structured in a way that supports reproducible science and downstream reuse [...]

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