A teaching and training framework to promote findable, accessible, interoperable, and reusable data generation in agriculture

Marrano, Annarita, Cabugos, Leyla, Hafner, Alenka, Kapoor, Beant, McNamara, John, O'Donnell, Megan, Reiser, Leonore, Tello-Ruiz, Marcela Karey, Zhang, Huiting, Staton, Margaret (April 2025) A teaching and training framework to promote findable, accessible, interoperable, and reusable data generation in agriculture. Database : the journal of biological databases and curation, 2025. ISSN 1758-0463 (Public Dataset)

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DOI: 10.1093/database/baaf034

Abstract

Advances in agricultural genetic, genomic, and breeding (GGB) technologies generate increasingly large and complex datasets that need to be adequately managed and shared. While several agricultural biological databases maintain and curate GGB data, not all scientists are aware of them and how they can be used to access and share data. In addition, there is the need to increase scientists' awareness that appropriate data archiving and curation increases data longevity and value and bolsters scientific discoveries' reproducibility and transparency. The AgBioData Education working group aims to address these unmet needs and developed a modular curriculum for educators teaching the basics of biological databases and the findable, accessible, interoperable, and reusable (FAIR) principles to undergraduate and graduate students (https://www.agbiodata.org/). The present paper provides an overview of the topics covered within the curriculum, called 'AgBioData Curriculum for Ag FAIR Data,' its audience and modalities, and how it will positively impact all the different stakeholders of the agricultural database ecosystem. We hope the modular curriculum presented here can help scientists and students understand and support database use in all aspects of improving our global food system.

Item Type:	Paper
Subjects:	bioinformatics
CSHL Authors:	Tello-Ruiz, Marcella
Communities:	CSHL labs > Ware lab
SWORD Depositor:	CSHL Elements
Depositing User:	CSHL Elements
Date:	25 April 2025
Date Deposited:	12 May 2025 12:22
Last Modified:	12 May 2025 12:22
Related URLs:	Publisher
Dataset ID:	https://zenodo.org/records/14278084
URI:	https://repository.cshl.edu/id/eprint/41868

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