Scientific Data (May 2024)

From Planning Stage Towards FAIR Data: A Practical Metadatasheet For Biomedical Scientists

  • Lea Seep,
  • Stephan Grein,
  • Iva Splichalova,
  • Danli Ran,
  • Mickel Mikhael,
  • Staffan Hildebrand,
  • Mario Lauterbach,
  • Karsten Hiller,
  • Dalila Juliana Silva Ribeiro,
  • Katharina Sieckmann,
  • Ronja Kardinal,
  • Hao Huang,
  • Jiangyan Yu,
  • Sebastian Kallabis,
  • Janina Behrens,
  • Andreas Till,
  • Viktoriya Peeva,
  • Akim Strohmeyer,
  • Johanna Bruder,
  • Tobias Blum,
  • Ana Soriano-Arroquia,
  • Dominik Tischer,
  • Katharina Kuellmer,
  • Yuanfang Li,
  • Marc Beyer,
  • Anne-Kathrin Gellner,
  • Tobias Fromme,
  • Henning Wackerhage,
  • Martin Klingenspor,
  • Wiebke K. Fenske,
  • Ludger Scheja,
  • Felix Meissner,
  • Andreas Schlitzer,
  • Elvira Mass,
  • Dagmar Wachten,
  • Eicke Latz,
  • Alexander Pfeifer,
  • Jan Hasenauer

DOI
https://doi.org/10.1038/s41597-024-03349-2
Journal volume & issue
Vol. 11, no. 1
pp. 1 – 14

Abstract

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Abstract Datasets consist of measurement data and metadata. Metadata provides context, essential for understanding and (re-)using data. Various metadata standards exist for different methods, systems and contexts. However, relevant information resides at differing stages across the data-lifecycle. Often, this information is defined and standardized only at publication stage, which can lead to data loss and workload increase. In this study, we developed Metadatasheet, a metadata standard based on interviews with members of two biomedical consortia and systematic screening of data repositories. It aligns with the data-lifecycle allowing synchronous metadata recording within Microsoft Excel, a widespread data recording software. Additionally, we provide an implementation, the Metadata Workbook, that offers user-friendly features like automation, dynamic adaption, metadata integrity checks, and export options for various metadata standards. By design and due to its extensive documentation, the proposed metadata standard simplifies recording and structuring of metadata for biomedical scientists, promoting practicality and convenience in data management. This framework can accelerate scientific progress by enhancing collaboration and knowledge transfer throughout the intermediate steps of data creation.