生物多样性基因组学最佳实践数据管理之旅。

IF 5.5 1区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY
Natalie J Forsdick, Jana Wold, Anton Angelo, François Bissey, Jamie Hart, Mitchell Head, Libby Liggins, Dinindu Senanayake, Tammy E Steeves
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引用次数: 0

摘要

测序技术的进步和成本的下降正在增加大规模生物多样性基因组数据集的可访问性。为了最大限度地发挥这些数据的影响,谨慎、深思熟虑的数据管理方法至关重要。然而,与此类数据集的管理相关的挑战仍然存在,研究界对什么是最佳实践的不确定性加剧了这一挑战。作为一个拥有丰富数据管理经验的跨学科团队,我们认识到,越来越需要全面的数据管理实践指导,以最大限度地降低数据丢失风险,最大限度地提高独立项目的效率,增加数据重用的机会,促进土著数据主权,并维护公平和关爱指导原则。在这里,我们描述了四个虚构的人物角色,反映了不同的用户数据管理体验,以确定生物多样性基因组学研究生态系统中的数据管理挑战。然后,我们使用这些人物角色来展示生物多样性基因组数据管理的现实考虑、妥协和行动。我们还启动了生物多样性基因组学数据管理中心(https://genomicsaotearoa.github.io/data-management-resources/),包含支持生物多样性基因组学研究人员,特别是那些刚接触数据管理的研究人员,走向最佳实践的技巧、技巧和资源。该中心还为那些专业知识超越基因组学并热衷于推进数据管理之旅的生物多样性研究人员提供了一个机会。我们的目标是支持生物多样性基因组学社区在整个研究生命周期中嵌入数据管理,以最大限度地提高研究影响和结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Journeying towards best practice data management in biodiversity genomics.

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.

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来源期刊
Molecular Ecology Resources
Molecular Ecology Resources 生物-进化生物学
CiteScore
15.60
自引率
5.20%
发文量
170
审稿时长
3 months
期刊介绍: Molecular Ecology Resources promotes the creation of comprehensive resources for the scientific community, encompassing computer programs, statistical and molecular advancements, and a diverse array of molecular tools. Serving as a conduit for disseminating these resources, the journal targets a broad audience of researchers in the fields of evolution, ecology, and conservation. Articles in Molecular Ecology Resources are crafted to support investigations tackling significant questions within these disciplines. In addition to original resource articles, Molecular Ecology Resources features Reviews, Opinions, and Comments relevant to the field. The journal also periodically releases Special Issues focusing on resource development within specific areas.
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