Data Management and Analysis Core

摘要/摘要 数据管理和分析核心(DMAC)将提供数据管理、生物统计、生物信息学、 和地理信息系统(GIS)支持和确保资源共享和科学的可重现性 所有四个项目和该计划支持的所有核心。除了这种支持，核心教职员工和研究人员 将从事与任务相关的研究，开发综合高维曝光的方法， 分子和表型数据。数据管理和资源共享活动将跨越以下三个原则 可再现性：(1)数据可再现性，包括数据管理计划和其他质量保证/ 所有中心数据的质量控制程序，(2)分析重现性，这将分析符合以下条件的方案 预先指定的、标准化的、严格的，以及(3)通过资源共享计划实现的结果可复制性 满足数据可查找、可访问、可互操作和可重复使用(公平)的预期原则 在美国国立卫生研究院数据科学战略计划中引入。DMAC将直接支持四个中心 项目，帮助行政和CEC核心将从尖端获得的复杂研究成果转化为 方法，以便于理解和易于可视化的结果总结，并与RETCC合作提供 对从事生物统计学领域中心相关项目的中心教职员工、学生和研究员进行培训， 定量基因组学和数据科学，包括促进可再生性和可复制性的方法。穿过 作为其活动的一部分，DMAC将促进和实现该中心 生物医学、环境科学和工程项目以及该中心与更广泛的 科学界，加速中心研究的影响。

SUMMARY/ ABSTRACT The Data Management and Analysis Core (DMAC) will provide data management, biostatistical, bioinformatics, and geographical information system (GIS) support and ensure resource sharing and reproducible science for all four projects and all cores supported by the program. In addition to this support, core faculty and researchers will engage in mission-related research that will develop methods to integrate high dimensional exposure, molecular, and phenotypic data. Data management and resource sharing activities will span three tenets of reproducibility: (1) data reproducibility, which will include data management plans and other quality assurance / quality control procedures for all Center data, (2) analysis reproducibility, which will analysis protocols that are pre-specified, standardized, and rigorous, and (3) result replicability, accomplished by a resource sharing plan that meets the desired principle of data being Findable, Accessible, Interoperable, and Reusable (FAIR) introduced in the NIH Data Science Strategic Plan. The DMAC will directly support each of the four Center projects, help the Administrative and CEC Cores translate complex research findings obtained from cutting-edge methodology to easily-understood and easily-visualized result summaries, and work with the RETCC to provide training to Center faculty, students, and fellows working on Center-related projects in the areas of biostatistics, quantitative genomics, and data science, including methods to promote reproducibility and replicability. Through its activities, DMAC will foster and enable the interoperability of data and methods between the Center’s biomedical and environmental science and engineering projects as well as between this Center and the broader scientific community, accelerating the impact of the Center's research.