Published September 12, 2023 | Version v1
Poster Open

Combining the BIDS and ARC Directory Structures for Multimodal Research Data Organization

  • 1. Combinatorial NeuroImaging Core Facility, Leibniz Institute for Neurobiology, Magdeburg, Germany
  • 2. Data Science and Management, Cluster of Excellence on Plant Sciences (CEPLAS), University of Cologne
  • 3. Imaging Facility, Cellular Stress Responses in Aging-Associated Diseases (CECAD), Cologne, University of Cologne, Germany
  • 4. Regional Computing Centre (RRZK), University of Cologne
  • 5. Big Data Analytics Working Group, Forschungszentrum Jülich, Germany
  • 6. Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau, Germany
  • 7. Albert-Ludwigs-Universität Freiburg, Germany


Interdisciplinary collaboration and integration of large and diverse datasets are becoming increasingly important. Answering complex research questions requires combining and analysing multimodal datasets. Research data management follows the FAIR principles making data findable, accessible, interoperable, and reusable. However, there are challenges in capturing the entire research cycle and contextualizing data according, not only for the DataPLANT and NFDI4BIOIMAGE communities. To address these challenges, DataPLANT developed a data structure called Annotated Research Context (ARC). The Brain Imaging Data Structure (BIDS) originated from the neuroimaging community extended for microscopic image data. Both concepts provide standardised and file system based data storage structures for organising and sharing research data accompanied with metadata. We exemplarily compare the ARC and BIDS designs and propose structural and metadata mapping.



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