From Planning Stage Towards FAIR Data: A Practical Metadatasheet For Biomedical Scientists
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Published:2024-05-22
Issue:1
Volume:11
Page:
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ISSN:2052-4463
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Container-title:Scientific Data
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language:en
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Short-container-title:Sci Data
Author:
Seep LeaORCID, Grein Stephan, Splichalova Iva, Ran Danli, Mikhael Mickel, Hildebrand Staffan, Lauterbach Mario, Hiller KarstenORCID, Ribeiro Dalila Juliana Silva, Sieckmann KatharinaORCID, Kardinal Ronja, Huang HaoORCID, Yu Jiangyan, Kallabis Sebastian, Behrens Janina, Till Andreas, Peeva Viktoriya, Strohmeyer Akim, Bruder Johanna, Blum Tobias, Soriano-Arroquia Ana, Tischer Dominik, Kuellmer Katharina, Li Yuanfang, Beyer MarcORCID, Gellner Anne-Kathrin, Fromme Tobias, Wackerhage Henning, Klingenspor Martin, Fenske Wiebke K., Scheja Ludger, Meissner Felix, Schlitzer Andreas, Mass ElviraORCID, Wachten DagmarORCID, Latz Eicke, Pfeifer Alexander, Hasenauer Jan
Abstract
AbstractDatasets 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.
Publisher
Springer Science and Business Media LLC
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