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

在为HEAL设计和实施数据管理和共享策略时，最大的挑战可能是其广泛的计划、项目和收集的数据类型。虽然单个计划或项目由数据协调中心（dcc）和数据管理中心（dmc）支持，但广泛共享HEAL数据将需要一个平台，该平台可以将dmc连接在一起，并在与它们顺利合作的同时扩展其范围。HEAL数据类型的范围很广，跨越多种测量模式（例如，临床数据、生物测定、可穿戴设备和自我报告数据），并且在大小和复杂性上有所不同。此外，不仅是HEAL研究人员，而且可能使用HEAL数据的其他研究人员所代表的科学学科的范围，以及可能追求的科学问题的范围，也对如何组织、记录和获取数据以最大限度地发挥其科学价值产生影响。具体来说，单个单片系统可能会失败，或者至少不是最优的。同时，要求所有的程序或项目按照一组共同的需求来构建它们自己的系统既昂贵又不可持续。我们建议建立和维护一个HEAL平台，该平台将与dmc互操作，使存储在dmc或其他存储库中的HEAL数据能够被发现和访问。该平台将允许搜索和查询HEAL元数据，以及研究内部和跨研究的选定数据，并提供对安全、可扩展的计算环境的访问，以便对HEAL数据以及用户自己的数据进行独立分析。

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.