Initiatives

GHGA – The German Human Genome-Phenome Archive – is building a secure national omics data infrastructure, enabling the use of human genome data for research purposes while preventing data misuse. GHGA is funded via the German program for research data infrastructures (NFDI) and is coordinated at the DKFZ.
It serves as German's national node both within the federated European Genome-Phenome Archive (EGA) as well as the German node in the European Genomic Data Infrastructure (GDI). Nationally it has been mandated as the data infrastructure for secondary use of genomics and related data but key projects such as the German National Cohort (NAKO) and the German model project genome sequencing (genom.de).

Research Data Management for Microscopy and Bioimage Analysis

Bioimaging based on light and electron microscopy comprises various powerful technologies for studying biological processes with high spatial and temporal resolution. Advanced bioimaging methods and bioimage analysis play a crucial role in biomedical research including cancer research. However, most bioimaging data are stored in proprietary file formats, can be of considerable size, and often lack standardized metadata. This makes it challenging for researchers to manage and share bioimaging data in compliance with the FAIR principles. NFDI4BIOIMAGE, a consortium within Germany’s National Research Data Infrastructure (NFDI), brings together expertise from universities and research institutions across Germany to address these challenges. The DKFZ German Cancer Research Center ico-coordinates the consortium’s work and develops novel tools and solutions for multimodal data integration. In close collaboration with international partners, NFDI4BIOIMAGE enhances the capacity and capabilities of bioimaging research data management – by the community for the community.

NFDI for Immunology 

The immune system plays a fundamental role in health and disease and efficiently protects vertebrate hosts from infections and cancer. However, failures in its regulation can cause autoimmunity, allergy, immunodeficiencies and malignancies. To understand the mechanisms underlying these processes and how they can be manipulated for the benefit of humans and animals, immunologists use a wide range of experimental methods. The efficient handling of thereby generated data, so that they meet the scientific demands for reproducibility and reusability, is currently one of the key challenges for immunological research.
As one of the 26 NFDI consortia, NFDI4Immuno aims to initiate and shape the necessary transformation process together with its community. DKFZ and its 14 partner institutions (nine co-applicants and five participants) ensure the broad anchoring in the scientific community as a whole as well as in the respective thematic domains.

Helmholtz Imaging’s mission is to unlock the potential of imaging in the Helmholtz Association. Image data provide a substantial part of data being generated in scientific research. Helmholtz Imaging is the overarching platform to better leverage and make accessible to everyone the innovative modalities, methodological richness, and data treasures of the Helmholtz Association.
For us, imaging is the whole process from data acquisition and data preparation to data management and data analysis. For this reason, we feel that the anchoring at the three host centers DESY, DKFZ and MDC is optimal to serve the entire imaging pipeline and jointly generate the greatest possible added value for the entire association. We are dedicated to making Helmholtz Imaging an internationally visible platform for imaging research.
Helmholtz Imaging is one of five platforms (HIDA, HIFIS, Helmholtz.AI and HMC) initiated by the Helmholtz Information & Data Science Incubator.

Helmholtz Imaging at DKFZ: Advancing AI for Image Analysis

At the German Cancer Research Center (DKFZ), Helmholtz Imaging pioneers research and support efforts to drive innovation in AI-powered image analysis. The DKFZ Research Unit tackles fundamental challenges in AI through three focus areas: Image Analysis, enhancing algorithmic understanding and generalizability; Human-Machine Interaction, ensuring safe and reliable AI integration; and Validation & Benchmarking, standardizing evaluation practices for robust and reproducible research. Complementing this, the Applied Computer Vision Lab provides hands-on support by developing tailored AI solutions, facilitating data annotation, and advancing evaluation methodologies. Together, these initiatives aim to bridge the gap between cutting-edge AI research and practical applications, empowering researchers across Helmholtz and beyond to extract meaningful insights from complex image data.

The aim of the Helmholtz Information & Data Science School for Health (HIDSS4Health) is to attract, promote and train the best young talents at the interface between data science and health-related applications. HIDSS4Health offers a structured doctoral training program embedded in a highly interdisciplinary research environment, bringing together experts from the data and life sciences. The scientific curriculum is complemented by training measures that provide doctoral researchers with the key qualifications expected from future leaders in science and industry.

The Helmholtz Metadata Collaboration (HMC) aims to improve the quality and usability of research data through standardized metadata. HMC is part of the Helmholtz Information and Data Science framework. It develops and implements novel concepts and technologies for sustainable research data handling through high-quality metadata. Its main goal is to make the depth and breadth of research data produced by Helmholtz Centres findable, accessible, interoperable, and reusable (FAIR) for the whole science community.
The HMC Hub Health is anchored at DKFZ and connects local activities in Digital Oncology with other Helmholtz centers in the research field of health. By linking with national and international networks like NFDI and EOSC, the HMC Hub Health facilitates the exchange of knowledge, expertise, and best practices, contributing to the advancement of the Digital Oncology program.