Roche Pharma Research and Early Development, Data & Analytics, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd, Basel, Switzerland.
Neuro-Behavioral Analysis Unit, Faculty of Biology & Medicine, University of Lausanne, Lausanne, Switzerland.
Lab Anim (NY). 2024 Mar;53(3):67-79. doi: 10.1038/s41684-024-01335-0. Epub 2024 Mar 4.
Although biomedical research is experiencing a data explosion, the accumulation of vast quantities of data alone does not guarantee a primary objective for science: building upon existing knowledge. Data collected that lack appropriate metadata cannot be fully interrogated or integrated into new research projects, leading to wasted resources and missed opportunities for data repurposing. This issue is particularly acute for research using animals, where concerns regarding data reproducibility and ensuring animal welfare are paramount. Here, to address this problem, we propose a minimal metadata set (MNMS) designed to enable the repurposing of in vivo data. MNMS aligns with an existing validated guideline for reporting in vivo data (ARRIVE 2.0) and contributes to making in vivo data FAIR-compliant. Scenarios where MNMS should be implemented in diverse research environments are presented, highlighting opportunities and challenges for data repurposing at different scales. We conclude with a 'call for action' to key stakeholders in biomedical research to adopt and apply MNMS to accelerate both the advancement of knowledge and the betterment of animal welfare.
尽管生物医学研究正经历着数据爆炸,但仅积累大量数据并不能保证科学的一个主要目标:在现有知识的基础上进一步发展。缺乏适当元数据的数据无法进行全面查询或整合到新的研究项目中,导致资源浪费和错失数据再利用的机会。对于使用动物进行的研究,这个问题尤为突出,因为人们对数据的可重复性和确保动物福利极为关注。在这里,为了解决这个问题,我们提出了一个最小元数据集 (MNMS),旨在实现体内数据的再利用。MNMS 与现有的体内数据报告验证指南 (ARRIVE 2.0) 一致,并有助于使体内数据符合 FAIR 标准。本文介绍了在不同研究环境中实施 MNMS 的场景,强调了在不同规模上进行数据再利用的机会和挑战。最后,我们呼吁生物医学研究的主要利益相关者采用和应用 MNMS,以加速知识的进步和动物福利的改善。