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

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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.