Data Management Core

数据管理核心

• 批准号: 10472039
• 负责人: Justin Guinney
• 金额: $ 134.38万
• 依托单位: CHILDREN'S HOSP OF PHILADELPHIA
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-26 至 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10472039
• 关键词: Accent; Address; Area; Automobile Driving; Bioinformatics; Biomedical Research; Clinical; Clinical Data; Collaborations; Collection; Communities; Complex; Consensus; Data; Data Analyses; Data Collection; Data Coordinating Center; Data Discovery; Data Management Resources; Data Pooling; Development; Disease; Down Syndrome; Elements; Ensure; Environment; FAIR principles; Foundations; Funding; Goals; Human Resources; Individual; Ingestion; Investigation; Leadership; Longevity; Maps; Metadata; Mission; Molecular; Multiomic Data; Pathway interactions; Persons; Phenotype; Play; Population; Positioning Attribute; Process; Publishing; Quality Control; Reporting; Research; Research Project Grants; Resources; Role; Secure; Site; Source; Standardization; Stress Tests; Structure; Technology; United States National Institutes of Health; Validation; Vision; Work; biobank; cloud based; cohort; community building; comorbidity; computerized data processing; dashboard; data ecosystem; data exchange; data harmonization; data ingestion; data management; data modeling; data portal; data quality; data resource; data sharing; data sharing networks; data standards; diverse data; experience; human disease; improved outcome; innovation; insight; interoperability; member; molecular imaging; multiple data types; novel; outreach; repository; trait; virtual; working group

PROJECT SUMMARY - Data Management Core. The key objective of the Data Management Core (DMC) of the INCLUDE Data Coordinating Center (DCC) is to develop and sustain data sharing pathways to fulfill the Center’s mission to study a large cohort of people with Down syndrome (DS) to accelerate research in the mechanisms driving and modulating comorbidities in this population. The DMC will build upon the processes and platforms we have deployed in prior DCCs to facilitate the data ingestion and harmonization of high priority clinical, biospecimen, and molecular data identified by the INCLUDE community. Our vision - shared and augmented by our partner teams in the DCC cores - is to ensure that data from INCLUDE cohorts are highly accessible and (re)usable by the research community to drive integrative and innovative approaches to DS research, and to spark insights from and within adjacent domains with shared biomolecular and phenotypic traits. To accomplish this ambitious goal, we will first develop a data governance structure to maximize use and re-use of INCLUDE data in order to address disparities and improve outcomes for people with DS . Second, in coordination with INCLUDE stakeholders, we will document use-cases to ensure the activities of the DCC reflect the priorities and concerns of the DS community, and map these use-cases to data models and standards to support the harmonization and interoperability of INCLUDE data. We will leverage and extend existing data models from the biomedical commons communities, and define quality control metrics for INCLUDE data types. Third, we will enhance our platform interfaces to support the transfer, validation, and aggregation of INCLUDE data within our data management system. DMC personnel will work hand-in-hand with data contributors to ensure the rapid and conformant transfer of multiple data types. Fourth, we will develop bioinformatic workflows and pipelines for the standardized processing of INCLUDE data within an integrated and highly scalable compute environment. Fifth, we will build and deploy a virtual biorepository to enable federated biospecimen sharing across the INCLUDE network and the DS research community. The DMC team - in close coordination with the Administrative and Outreach Core and the Data Portal Core - will leverage our deep experience in data management and coordination, community building, and biomedical research to create a world-class resource for data sharing, access, and integrative analysis that would enable novel investigations into DS and its comorbidities across the lifespan.

项目摘要-数据管理核心。 包括数据协调中心(DCC)的数据管理核心(DMC)的主要目标是 开发和维持数据共享途径，以完成中心研究具有以下特点的大量人群的使命 唐氏综合征(DS)加速研究驱动和调节本病共病的机制 人口。公契将建立在我们在以前的公关中心部署的流程和平台的基础上，以促进 高优先级临床、生物医学和分子数据的数据摄取和协调 包括社区。我们的愿景-由我们在DCC核心的合作伙伴团队共享和增强-是确保 来自包括队列的数据是高度可访问的，并且(可重复)由研究社区用于驾驶 综合和创新的方法进行DS研究，并激发来自相邻领域和内部的见解 具有共同的生物分子和表型特征。 为了实现这一雄心勃勃的目标，我们将首先开发一个数据治理结构，以最大限度地利用和重用 包括数据，以便解决差异并改善DS患者的结果。第二，在 与包括利益相关者的协调，我们将记录用例，以确保DCC的活动反映 DS社区的优先事项和关注事项，并将这些用例映射到数据模型和标准，以 支持包括数据的协调和互操作性。我们将利用和扩展现有数据 来自生物医学共享社区的模型，并定义包括数据类型的质量控制度量。 第三，我们将增强我们的平台接口，以支持传输、验证和聚合 我们的数据管理系统中的数据。DMC人员将与数据贡献者携手合作，以 确保快速、一致地传输多种数据类型。第四，发展生物信息化工作流程 用于标准化处理的管道包括集成且高度可扩展的计算中的数据 环境。第五，我们将构建和部署一个虚拟生物库，以实现联合生物谱系共享 通过INCLUDE网络和DS研究社区。 民主变革管理中心团队--与行政和外联核心以及数据门户核心密切协调--将 利用我们在数据管理和协调、社区建设和生物医学方面的丰富经验 研究创建用于数据共享、访问和集成分析的世界级资源，从而实现 对DS及其终生合并症的新调查。