A Framework for Automated and Reproducible Geomarker Curation and Computation at Scale

项目摘要 环境暴露和社区特征，包括空气污染、绿地、犯罪和指数 社区贫困是健康的有力预测因素。这些数据被称为“地理标志”，直到最近 体验到了有限的可用性。“大数据”的民主化和地理信息学的进步现在允许 史无前例的通达，为将“精准医疗”拓展为“精准公共健康”铺平了道路。 将这些新获得的数据自动链接到现有研究和电子健康记录(EHR)数据库， 然而，由于数据在时空分辨率和范围方面异质性，fi分类通常是不同的。 表示、存储、格式、检索方法和计算策略。这阻碍了数据的可访问性和 互操作性。由于精确的地理位置被认为是受保护的健康信息(PHI)，因此研究规则- 旨在保护研究参与者身份的措施往往会给共享数据和利用数据带来障碍 第三方工具。因此，尽管这些数据的使用正在迅速扩大，但它们在研究和临床上的应用 护理受到获得适当专业知识和依赖INFfi有效的手动数据管理的阻碍。我们正在紧要关头 缺少方法和工具，无法使可重现的地理标志评估更容易获得和使用 由生物医学研究人员提供。为了解决这一限制，我们的总体目标是制定一项经过策划的标准- 研究人员可用于将地理标志与其地理标志进行有效、自动和可重现的链接的程序库 以及一个通用的框架，暴露评估的科学家可以对此做出贡献。我们将创造 基于软件集装化和自动化元数据收集和发布的初始库，进行 在现有电子健康记录信息学数据流水线中的测试实现，并获得反馈 来自用户和消费者。重要的是，该提案将为地理标志工具开发创建一个框架 这将允许任何用户以一致和用户友好的方式与软件交互。发展将需要 公开放置，这样任何人都可以提供反馈和莫迪fi阳离子或添加到我们的工具集。软性的- 软件、框架和容器库将免费并开放源码。我们的努力将使地理标志数据和 方法更加fi可接受、可访问、可互操作和可重用(公平)，并随着我们寻求使我们的方法 一种被广泛采用、社区维护和可持续的资源，以推动精准公众的进步 健康。

Project Summary Environmental exposures and community characteristics, including air pollution, greenspace, crime, and indices of community deprivation are powerful predictors of health. These data, termed ”geomarkers”, have until recently experienced limited availability. Democratization of “big spatial data” and advances in geoinformatics now allow unprecedented access, paving the way for the expansion of “precision medicine” into “precision public health”. Automated linkage of these newly available data to existing studies and electronic health record (EHR) databases, however, is often difficult due to data heterogeneity with respect to spatiotemporal resolution and extent, anno- tation, storage, formats, retrieval methods, and computational strategies. This hinders data accessibility and interoperability. Because precise geolocation is considered protected health information (PHI), research regula- tions designed to protect the identities of study participants often present obstacles to sharing data and utilizing third party tools. Thus, though usage of these data is rapidly expanding, their application in research and clinical care is hampered by access to proper expertise and reliance on inefficient manual data curation. We are critically missing the methods and tools to make reproducible geomarker assessment widely accessible and easily used by biomedical researchers. To address this limitation, our overall objective is to develop a curated and standard- ized library that researchers can use for efficient, automated, and reproducible linkage of geomarkers to their own data and a generalized framework to which exposure assessment scientists can contribute. We will create an initial library based on software containerization and automated metatdata collection and publishing, conduct a test implementation within an existing electronic health record informatics data pipeline, and obtain feedback from users and consumers. Importantly, this proposal will create a framework for geomarker tool development that will allow any user to interact with the software in a consistent and user friendly way. Development will take place publicly such that anyone can provide feedback and modifications or additions to our toolset. The soft- ware, framework, and library of containers will free and open source. Our efforts will make geomarker data and methods more findable, accessible, interoperable, and reusable (FAIR) and as we seek to make our approach a widely-adopted, community-maintained, and sustainable resource to fuel the advancement of precision public health.