The future is FAIR: a community framework for enhanced data management and data sharing

Marrano, Annarita, Andorf, Carson, Campbell, Jacqueline D, Cannon, Ethalinda, Coe, Michael, Cooper, Laurel, Dyer, Sarah, Harrison, Peter W, Kumari, Sunita, Jung, Sook, Main, Dorrie, McNamara, John, Molik, David, Naithani, Sushma, Poelchau, Monica F, Staton, Margaret E, Selby, Peter, Sen, Taner Z, Tello-Ruiz, Marcela K, Reiser, Leonore, Working group members (January 2026) The future is FAIR: a community framework for enhanced data management and data sharing. Database : the journal of biological databases and curation, 2026. ISSN 1758-0463

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URL: https://www.ncbi.nlm.nih.gov/pubmed/42788682

DOI: 10.1093/database/baag058

Abstract

The AgBioData consortium is a community-driven initiative supporting >40 genomic, genetic, and breeding (GGB) databases for agricultural research. Informed by the FAIR (Findable, Accessible, Interoperable, and Reusable) data principles, AgBioData aims to improve data management, sharing, and reuse across diverse biological data types. Through a National Science Foundation Research Coordination Network grant (award #2126334), the consortium engaged stakeholders via working groups, webinars, and community workshops to identify key data challenges and develop recommendations, tools, and training materials. Major outcomes include guidelines for standardizing genetic and genomic data, SNP harmonization protocols, recommendations for ontology usage, and an open-access curriculum for FAIR data literacy. Other key topics addressed in the first 3 years include data federation, improved single-cell data annotation, and advanced database interoperability. Surveys indicate an increase in community awareness and adoption of FAIR practices. AgBioData represents a scalable model for enhancing agricultural data infrastructure and sustainability, with ongoing efforts focused on AI readiness and the long-term support of curated data resources.

Item Type:	Paper
Subjects:	bioinformatics bioinformatics > genomics and proteomics
CSHL Authors:	Kumari, Sunita Tello-Ruiz, Marcella
Communities:	CSHL labs > Ware lab
SWORD Depositor:	CSHL Elements
Depositing User:	CSHL Elements
Date:	15 January 2026
Date Deposited:	28 Sep 2026 16:21
Last Modified:	28 Sep 2026 16:21
PMCID:	PMC13613210
Related URLs:	Publisher
URI:	https://repository.cshl.edu/id/eprint/42327

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