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

大规模自动化、可重复地理标记管理和计算的框架

• 批准号: 10663308
• 负责人: Cole Brokamp
• 金额: $ 33.79万
• 依托单位: CINCINNATI CHILDRENS HOSP MED CTR
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-01 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10663308
• 关键词: Acceleration; Address; Adopted; Air Pollution; Biomedical Research; Characteristics; Code; Collaborations; Collection; Communities; Computer software; Crime; Data; Data Linkages; Data Set; Databases; Decentralization; Democracy; Development; Disease; Documentation; Ecosystem; Electronic Health Record; Environmental Exposure; FAIR principles; Feedback; Free Will; Future; Goals; Green space; Guidelines; Health; Health protection; Image; Incidence; Informatics; Knowledge; Libraries; Manuals; Measures; Metadata; Methods; Modification; Outcome; Output; Participant; Privacy; Process; Public Health; Public Health Informatics; Publishing; Pythons; Regulation; Reproducibility; Research; Research Personnel; Resolution; Retrieval; Scientist; Secure; Services; Site; Specific qualifier value; Standardization; Testing; Work; biomedical informatics; clinical care; computer framework; computerized tools; cost effectiveness; data curation; data pipeline; data sharing; data tools; deprivation; design; digital; experience; heterogenous data; improved; indexing; interoperability; iterative design; novel; open source; open source library; precision medicine; privacy protection; research study; spatiotemporal; statistics; sustainability framework; sustainable resource; tool; tool development; user-friendly

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.

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 是健康状况的有力预测指标。这些数据，被称为“地理标志”，直到最近， 体验有限的可用性。“大空间数据”的民主化和地理信息学的进步现在允许 这是前所未有的，为“精准医疗”扩展到“精准公共卫生”铺平了道路。 将这些新获得的数据自动链接到现有的研究和电子健康记录（EHR）数据库， 然而，由于时空分辨率和范围方面的数据异质性， 站点、存储、格式、检索方法和计算策略。这阻碍了数据的可访问性， 互用性由于精确的地理位置被认为是受保护的健康信息（PHI），因此研究规定 旨在保护研究参与者身份的措施往往会阻碍数据共享和利用， 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中的应用 获得适当的专业知识和依赖效率低下的人工数据管理阻碍了护理。我们非常重视 缺乏使可复制的地质标志评估广泛获得和易于使用的方法和工具 被生物医学研究人员发现。为了解决这个问题，我们的总体目标是建立一个标准化和标准化的- 研究人员可以使用的高效，自动化和可复制的链接的地理标记，以他们的 这是一个可供风险评估科学家提供自己的数据和一个通用框架的框架。我们将创建 基于软件容器化和自动化元数据收集和发布的初始库， 在现有的电子健康记录信息学数据管道内进行测试，并获得反馈 从用户和消费者。重要的是，该提案将为地质标记工具的开发创建一个框架 这将允许任何用户以一致和用户友好的方式与软件交互。发展将采取 公开放置，以便任何人都可以提供反馈和修改或添加到我们的工具集。柔软的- 软件、框架和容器库将是免费和开源的。我们的努力将使地球标志数据， 方法更可查找、可访问、可互操作和可重用（FAIR），当我们寻求使我们的方法 一个广泛采用，社区维护和可持续的资源，以推动精确公共 健康