Advancing Image Data Interoperability and Standards within an NIH Ecosystem (AIDISNE): A CHOP, FlyWheel, and Seven Bridges Integration Demonstration Project

项目摘要 我们的研究计划包括三个组成部分，解决了端到端用例驱动的框架： (1)将演示通过集成飞轮来摄取、发布和请求成像数据 INCLUDE生态系统内的平台;（2）将提供平台和工作空间互操作性功能 CAVATICA和FlyWheel平台之间，以及（3）利用和支持进一步扩展DRS 和FHIR，以支持产次成像数据以及INCLUDE中的临床和基因组学数据 数据中心，FHIR优先门户。该研究计划旨在通过完成演示来解决成像差距 项目，进一步定义和描述了集成成像数据的可扩展要求， 现有NIH资助的生态系统，定义跨平台的最低互操作性要求， 通过开发功能实现，并将这些需求转化为最佳实践， 通过NIH云平台互操作性（NCPI）工作中的标准开发。

PROJECT SUMMARY Our research plan includes three components that address an end-to-end use-case-driven framework that: (1) will demonstrate the ingestion, publishing, and requisition of imaging data by integrating the FlyWheel Platform within the INCLUDE Ecosystem; (2) will provide for platform and workspace interoperability features between CAVATICA and the FlyWheel Platform, and (3) leverage and support the further extension DRS and FHIR to support imaging data in parity and alongside clinical and genomics data within the INCLUDE Data Hub, a FHIR-first portal. The research plan aims to address Imaging Gaps by completing demonstration projects that further define and delineate the extensible requirements for integrating imaging data with existing NIH-funded ecosystems, define minimal interoperability requirements across platforms and workspaces by developing functional implementations, and translating these requirements into best practice through standard development within the NIH Cloud Platform Interoperability (NCPI) effort.