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一种用于开发和验证云环境中人类基因组数据管理成熟度矩阵的混合方法方案。

A mixed-methods protocol to develop and validate a stewardship maturity matrix for human genomic data in the cloud.

作者信息

Rahimzadeh Vasiliki, Peng Ge, Cho Mildred

机构信息

Baylor College of Medicine, One Baylor Plaza, Houston, TX, (United States).

Earth System Science Center/NASA MSFC IMPACT, The University of Alabama in Huntsville, Huntsville, AL, (United States).

出版信息

Front Genet. 2022 Oct 14;13:876869. doi: 10.3389/fgene.2022.876869. eCollection 2022.

Abstract

This article describes a mixed-methods protocol to develop and test the implementation of a stewardship maturity matrix (SMM) for repositories which govern access to human genomic data in the cloud. It is anticipated that the cloud will host most human genomic and related health datasets generated as part of publicly funded research in the coming years. However, repository managers lack practical tools for identifying what stewardship outcomes matter most to key stakeholders as well as how to track progress on their stewardship goals over time. In this article we describe a protocol that combines Delphi survey methods with SMM modeling first introduced in the earth and planetary sciences to develop a stewardship impact assessment tool for repositories that manage access to human genomic data. We discuss the strengths and limitations of this mixed-methods design and offer points to consider for wrangling both quantitative and qualitative data to enhance rigor and representativeness. We conclude with how the empirical methods bridged in this protocol have potential to improve evaluation of data stewardship systems and better align them with diverse stakeholder values in genomic data science.

摘要

本文介绍了一种混合方法方案,用于开发和测试管理云中人基因组数据访问的存储库的管理成熟度矩阵(SMM)的实施情况。预计在未来几年,云将承载作为公共资助研究一部分生成的大多数人类基因组及相关健康数据集。然而,存储库管理者缺乏实用工具来确定哪些管理成果对关键利益相关者最为重要,以及如何随时间跟踪其管理目标的进展情况。在本文中,我们描述了一种方案,该方案将德尔菲调查方法与地球和行星科学中首次引入的SMM建模相结合,以开发一种用于管理人类基因组数据访问的存储库的管理影响评估工具。我们讨论了这种混合方法设计的优点和局限性,并提供了在处理定量和定性数据时需要考虑的要点,以提高严谨性和代表性。我们最后总结了本方案中采用的实证方法如何有可能改进数据管理系统的评估,并使其更好地与基因组数据科学中不同利益相关者的价值观保持一致。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3761/9614211/d8db5890a6b5/fgene-13-876869-g001.jpg

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