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Advances in sequencing technologies and declining costs are increasing the accessibility of large‐scale biodiversity genomic datasets. To maximize the impact of these data, a careful, considered approach to data management is essential. However, challenges associated with the management of such datasets remain, exacerbated by uncertainty among the research community as to what constitutes best practices. As an interdisciplinary team with diverse data management experience, we recognize the growing need for guidance on comprehensive data management practices that minimize the risks of data loss, maximize efficiency for stand‐alone projects, enhance opportunities for data reuse, facilitate Indigenous data sovereignty and uphold the FAIR and CARE Guiding Principles. Here, we describe four fictional personas reflecting differing user experiences with data management to identify data management challenges across the biodiversity genomics research ecosystem. We then use these personas to demonstrate realistic considerations, compromises and actions for biodiversity genomic data management. We also launch the Biodiversity Genomics Data Management Hub (https://genomicsaotearoa.github.io/data‐management‐resources/), containing tips, tricks and resources to support biodiversity genomics researchers, especially those new to data management, in their journey towards best practice. The Hub also provides an opportunity for those biodiversity researchers whose expertise lies beyond genomics and are keen to advance their data management journey. We aim to support the biodiversity genomics community in embedding data management throughout the research lifecycle to maximize research impact and outcomes. [ABSTRACT FROM AUTHOR]

Background This study explores a library-led research data management (RDM) training program at a Canadian post-secondary institution that targeted students participating in summer research assistantships as well as their faculty supervisors. This paper describes the program in detail and shares findings from a student reflection assignment about practicing RDM for the first time. Methods The RDM training program included four requirements: attending an introductory RDM session; attending a data management plan (DMP) workshop; submitting a DMP for feedback; and completing a reflection assignment. Where consent was obtained (n=19), reflection assignments were analyzed using a qualitative content analysis approach. Results 35 faculty supervisors registered 53 students to participate. 62.2% (n=33) of students completed all components of the program. Perceived benefits of completing a DMP included improved project planning, supporting best practices, potential for data reuse, and team communication. Perceived challenges included the inflexibility of DMPs, difficulty populating DMPs, demands on researchers’ time, and lack of long-term utility. 73.6% of students (n=14/19) reported that building a DMP helped them with their summer projects. Conclusion Through instruction, practical engagement, and reflection within the context of real-world research, the program supported participants in learning about and practicing RDM, and provided insights for academic librarians who wish to refine or develop training in their local contexts as they continue to navigate emerging expectations from funders and publishers.