This chapter provides a comprehensive overview of FAIR principles applied to omics data management, addressing key challenges in handling large-scale, heterogeneous datasets while promoting reproducibility, collaboration, and open science practices. It covers essential strategies including Data Management Plans (DMPs), file organization, metadata standards, ontologies, repository selection, interoperability protocols, and security measures for privacy and ethics compliance. Best practices are outlined for achieving Findable, Accessible, Interoperable, and Reusable data, with recommendations for continuous improvement to support cross-omics integration and long-term data stewardship.
Pina-Martins et al. (Thu,) studied this question.
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