Helping to End Addiction Long-term (HEAL) Data Platform

帮助戒除成瘾长期 (HEAL) 数据平台

• 批准号: 10906696
• 负责人: ROBERT L. GROSSMAN
• 金额: $ 593万
• 依托单位: UNIVERSITY OF CHICAGO
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10906696
• 关键词: Agreement; Architecture; Area; Basic Science; Biological Assay; Chicago; Child; Clinical Data; Clinical Trials; Collection; Complex; Contracts; Data; Data Analyses; Data Commons; Data Coordinating Center; Data Reporting; Data Security; Data Set; Data Sources; Development; Discipline; Documentation; Ecosystem; Educational workshop; Ensure; Environment; FAIR principles; Funding; Future; Genomic Data Commons; Grant; Helping to End Addiction Long-term; Heterogeneity; Individual; Information Systems; Laws; Link; Measurement; Metadata; Modality; National Heart, Lung, and Blood Institute; National Human Genome Research Institute; National Institute of Diabetes and Digestive and Kidney Diseases; National Institute of Drug Abuse; Observational Study; Pain; Pain Research; Pain management; Participant; Patient Self-Report; Phase; Policies; Procedures; Regulation; Research; Research Personnel; Research Project Grants; Research Support; Resources; Secure; Services; Source; System; Testing; Text; Time; Training; U-Series Cooperative Agreements; United States National Institutes of Health; Universities; Update; Work; anticancer research; catalyst; cloud based; data acquisition; data ecosystem; data management; data resource; data sharing; data tools; database of Genotypes and Phenotypes; design; flexibility; group competition; implementation framework; improved; large scale data; open source; opioid use disorder; petabyte; pre-clinical research; programs; repository; sharing platform; wearable device; webinar

Updated Abstract Text: Perhaps the biggest challenge in designing and implementing a data management & sharing strategy for HEAL is its broad range of programs, projects and types of data being collected. While individual programs or projects are supported by Data Coordinating Centers (DCCs) and Data Management Centers (DMCs), broad sharing of HEAL data will require a platform that can link together the DMCs and extend their reach while working smoothly with them. The range of HEAL data types is extensive, spanning multiple measurement modalities (e.g., clinical data, bioassays, wearables and self-report data) as well as varying in size and complexity. In addition, the range of scientific disciplines represented not only among the HEAL investigators but among other researchers likely to use HEAL data, together with the range of scientific questions that might be pursued, also have implications for how data should be organized, documented and made accessible to maximize their scientific value. Specifically, a single monolithic system is likely to fail, or at least be sub-optimal. At the same time, asking all programs or projects to build their own systems conforming to a set of common requirements would be both expensive and unsustainable. We propose to build and maintain a HEAL Platform that will interoperate with the DMCs to enable discoverability and access of HEAL data stored in the DMCs or other repositories. The platform will allow search and query of the HEAL metadata, and selected data, within and across studies, and provide access to a secure, scalable computing environment to conduct independent analysis on HEAL data along with the user’s own data.

更新的摘要文本：设计和实施Heal的数据管理和共享策略的最大挑战是其广泛的程序，项目和正在收集的数据类型。虽然数据协调中心（DCC）和数据管理中心（DMC）支持各个程序或项目，但HEAL数据的广泛共享将需要一个平台，该平台可以将DMC链接在一起并扩展其覆盖范围，同时与他们平稳合作。治愈数据类型的范围是广泛的，涵盖了多个测量方式（例如临床数据，生物测定，可穿戴设备和自我报告数据），以及大小和复杂性的变化。此外，科学学科的范围不仅代表了治疗研究人员之间的，而且还代表了可能使用Heal数据的其他研究人员，以及可能提出的科学问题的范围，也对应如何组织，记录和使其可访问数据以最大程度地提高其科学价值有影响。具体而言，单个整体系统可能会失败，或者至少是最佳的。同时，要求所有程序或项目构建自己的系统符合一系列共同要求的系统既昂贵又不可持续。我们建议建立和维护一个治疗平台，该平台将与DMC互操作，以实现DMCS或其他存储库中存储的Heal数据的可发现性和访问。该平台将允许在研究内和跨研究中对Heal Metadata的搜索和查询，并选择了所选数据，并提供对安全，可扩展的计算环境的访问权限，以对Heal Data进行独立的分析以及用户自己的数据。