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NFDI4BIOIMAGE
Published August 7, 2024 | Version v1
Proposal Open

NFDI4BIOIMAGE - National Research Data Infrastructure for Microscopy and Bioimage Analysis

Creators

  • 1. ROR icon German BioImaging – Gesellschaft für Mikroskopie und Bildanalyse
  • 2. ROR icon Osnabrück University
  • 3. ROR icon University of Freiburg
  • 4. University of Münster
  • 5. ROR icon German Cancer Research Center
  • 6. ROR icon Leibniz Institute for Neurobiology
  • 7. ROR icon Leibniz-Institut für Naturstoff-Forschung und Infektionsbiologie e. V. - Hans-Knöll-Institut (HKI)
  • 8. ROR icon European Molecular Biology Laboratory
  • 9. ROR icon Leipzig University
  • 10. ROR icon TU Dresden
  • 11. ROR icon University of Konstanz
  • 12. ROR icon Leibniz Institute for Plasma Science and Technology
  • 13. ROR icon Leibniz Institute of Photonic Technology
  • 14. ROR icon Helmholtz Centre for Environmental Research
  • 15. ROR icon Leibniz Institute for Analytical Sciences - ISAS
  • 16. ROR icon TU Dortmund University
  • 17. ROR icon Johannes Gutenberg University Mainz
  • 18. ROR icon Forschungszentrum Jülich
  • 19. ROR icon Max Planck Institute for Evolutionary Biology
  • 20. ROR icon University of Göttingen
  • 21. ROR icon Heidelberg University
  • 22. ROR icon Cologne Excellence Cluster on Cellular Stress Responses in Aging Associated Diseases
  • 23. ROR icon University of Cologne
  • 24. ROR icon University of Dundee
  • 25. ROR icon Heinrich Heine University Düsseldorf
  • 26. ROR icon Cluster of Excellence on Plant Sciences
  • 27. ROR icon European Bioinformatics Institute
  • 28. ROR icon Euro-BioImaging ERIC
  • 29. ROR icon Max Planck Institute for Multidisciplinary Sciences
  • 30. ROR icon Quantitative Biology Center
  • 31. ROR icon University of Tübingen
  • 32. ROR icon University of Duisburg-Essen

Description

Bioimaging refers to a collection of methods to visualize the internal structures and mechanisms of living organisms. The fundamental tool, the microscope, has enabled seminal discoveries like that of the cell as the smallest unit of life, and continues to expand our understanding of biological processes. Today, we can follow the interaction of single molecules within nanoseconds in a living cell, and the development of complete small organisms like fish and flies over several days starting from the fertilized egg. Each image pixel encodes multiple spatiotemporal and spectral dimensions, compounding the massive volume and complexity of bioimage data. Proper handling of this data is indispensable for analysis and its lack has become a growing hindrance for the many disciplines of the life and biomedical sciences relying on bioimaging. No single domain has the expertise to tackle this bottleneck alone.

As a method-specific consortium, NFDI4BIOMAGE seeks to address these issues, enabling bioimaging data to be shared and re-used like they are acquired, i.e., independently of disciplinary boundaries. We will provide solutions for exploiting the full information content of bioimage data and enable new discoveries through sharing and re-analysis. Our RDM strategy is based on a robust needs analysis that derives not only from a community survey but also from over a decade of experience in German BioImaging, the German Society for Microscopy and Image Analysis. It considers the entire lifecycle of bioimaging data, from acquisition to archiving, including analysis and enabling re-use. A foundational element of this strategy is the definition of a common, cloud-compatible, and interoperable digital object that bundles binary images with their descriptive and provenance metadata. With members from plant biology to neuroscience, NFDI4BIOIMAGE will champion the standardization of bioimage data to create a framework that answers discipline-specific needs while ensuring communication and interoperability with data types and RDM systems across domains. Integration of bioimage data with, e.g., omics data as the basis for spatial omics, holds great promise for fields such as cancer medicine. Unlocking the full potential of bioimage data will rely on the development and broad availability of exceptional analysis tools and training sets. NFDI4BIOIMAGE will make these accessible and usable including cutting-edge AI-based methods in scalable cloud environments. NFDI4BIOIMAGE intersects with multiple NFDI consortia, most prominently with GHGA for linking image and genomics data and with DataPLANT on the definition of FAIR data objects. Last but not least, NFDI4BIOIMAGE is internationally well connected and represents the opportunity for German scientists to keep path with and have a voice in several international initiatives focusing on the FAIRification of bioimage data as one of the main challenges for the advancement of knowledge in the life and biomedical sciences.

Notes

This document contains the grant application of the consortium initiative NFDI4BIOIMAGE with minor modifications. The original proposal was submitted to the DFG on November 2nd, 2021. 

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