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一本关于在团队科学背景下制定协调研究工作流程的指南.

Oscar E Ruiz1, Joost B Wagenaar2, Bella Mehta3

  • 1Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.

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概括
此摘要是机器生成的。

建立有效的数据协调框架对于大型团队科学项目至关重要. 这一观点为创建数据管道的指导提供了指导,用于跨不同研究团队的综合分析.

关键词:
大数据就是大数据.慢性疼痛是一种慢性疼痛.共同的数据元素数据统一和数据协调.数据整合数据集成关节疾病是一种关节疾病.一个元数据标准.团队科学 团队科学

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科学领域:

  • 多学科研究多学科研究.
  • 数据科学是数据科学.
  • 生物医学研究的研究.

背景情况:

  • 大规模的跨学科团队科学倡议对于解决复杂的科学问题至关重要.
  • 这些项目旨在通过先进的方法产生大型,协调的数据集,用于利用先进的方法进行突破性发现.
  • 协调各种数据集需要一个强大的支持框架,由所有参与成员构建.

研究的目的:

  • 为开发以研究为中心的数据收集和分析管道提供指导.
  • 为了使下游集成分析在内部和跨不同的团队.
  • 分享来自RESToring JOIN健康和功能减轻疼痛 (RE-JOIN) 联盟的集体经验.

主要方法:

  • 为跨团队沟通建立一个共同的语言.
  • 实施协调方法,协议和 (元数据) 标准.
  • 开发共同的数据元素和适当的数据协调基础设施.

主要成果:

  • 一个有效的数据协调框架需要买入,团队建设,以及所有成员的重大努力.
  • 数据协调的常见挑战往往独立于特定的研究问题或技术.
  • RE-JOIN联盟的经验强调了项目特定框架和流程的重要性.

结论:

  • 开发强大的数据协调框架对于大型团队科学计划的成功至关重要.
  • 为创建促进综合分析的数据管道提供了指导.
  • 合作和共同努力是克服复杂研究项目的数据整合挑战的关键.