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FAIR research data management as community approach in bioengineering
Research data management (RDM) requires standards, policies, and guidelines. Findable, accessible, interoperable, and reusable (FAIR) data management is critical for sustainable research. Therefore, collaborative approaches for managing FAIR‐structured data are becoming increasingly important for lo...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9815074/ https://www.ncbi.nlm.nih.gov/pubmed/36619883 http://dx.doi.org/10.1002/elsc.202200005 |
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author | Rehnert, Martina Takors, Ralf |
author_facet | Rehnert, Martina Takors, Ralf |
author_sort | Rehnert, Martina |
collection | PubMed |
description | Research data management (RDM) requires standards, policies, and guidelines. Findable, accessible, interoperable, and reusable (FAIR) data management is critical for sustainable research. Therefore, collaborative approaches for managing FAIR‐structured data are becoming increasingly important for long‐term, sustainable RDM. However, they are rather hesitantly applied in bioengineering. One of the reasons may be found in the interdisciplinary character of the research field. In addition, bioengineering as application of principles of biology and tools of process engineering, often have to meet different criteria. In consequence, RDM is complicated by the fact that researchers from different scientific institutions must meet the criteria of their home institution, which can lead to additional conflicts. Therefore, centrally provided general repositories implementing a collaborative approach that enables data storage from the outset In a biotechnology research network with over 20 tandem projects, it was demonstrated how FAIR‐RDM can be implemented through a collaborative approach and the use of a data structure. In addition, the importance of a structure within a repository was demonstrated to keep biotechnology research data available throughout the entire data lifecycle. Furthermore, the biotechnology research network highlighted the importance of a structure within a repository to keep research data available throughout the entire data lifecycle. |
format | Online Article Text |
id | pubmed-9815074 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-98150742023-01-05 FAIR research data management as community approach in bioengineering Rehnert, Martina Takors, Ralf Eng Life Sci Perspective Research data management (RDM) requires standards, policies, and guidelines. Findable, accessible, interoperable, and reusable (FAIR) data management is critical for sustainable research. Therefore, collaborative approaches for managing FAIR‐structured data are becoming increasingly important for long‐term, sustainable RDM. However, they are rather hesitantly applied in bioengineering. One of the reasons may be found in the interdisciplinary character of the research field. In addition, bioengineering as application of principles of biology and tools of process engineering, often have to meet different criteria. In consequence, RDM is complicated by the fact that researchers from different scientific institutions must meet the criteria of their home institution, which can lead to additional conflicts. Therefore, centrally provided general repositories implementing a collaborative approach that enables data storage from the outset In a biotechnology research network with over 20 tandem projects, it was demonstrated how FAIR‐RDM can be implemented through a collaborative approach and the use of a data structure. In addition, the importance of a structure within a repository was demonstrated to keep biotechnology research data available throughout the entire data lifecycle. Furthermore, the biotechnology research network highlighted the importance of a structure within a repository to keep research data available throughout the entire data lifecycle. John Wiley and Sons Inc. 2022-04-28 /pmc/articles/PMC9815074/ /pubmed/36619883 http://dx.doi.org/10.1002/elsc.202200005 Text en © 2022 The Authors. Engineering in Life Sciences published by Wiley‐VCH GmbH. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Perspective Rehnert, Martina Takors, Ralf FAIR research data management as community approach in bioengineering |
title | FAIR research data management as community approach in bioengineering |
title_full | FAIR research data management as community approach in bioengineering |
title_fullStr | FAIR research data management as community approach in bioengineering |
title_full_unstemmed | FAIR research data management as community approach in bioengineering |
title_short | FAIR research data management as community approach in bioengineering |
title_sort | fair research data management as community approach in bioengineering |
topic | Perspective |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9815074/ https://www.ncbi.nlm.nih.gov/pubmed/36619883 http://dx.doi.org/10.1002/elsc.202200005 |
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