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
基本信息
- 批准号:10452591
- 负责人:
- 金额:$ 33.79万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 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:
- 关键词:AddressAdoptedAir PollutionBiomedical ResearchCharacteristicsCodeCollaborationsCollectionCommunitiesComputer softwareCrimeDataData LinkagesData SetDatabasesDecentralizationDevelopmentDiseaseDocumentationEcosystemElectronic Health RecordEnsureEnvironmental ExposureFAIR principlesFeedbackFree WillFutureGoalsGreen spaceGuidelinesHealthIncidenceInformaticsKnowledgeLibrariesManualsMeasuresMetadataMethodsModificationOutcomeOutputParticipantPrivacyProcessPublic HealthPublic Health InformaticsPublishingPythonsRegulationReproducibilityResearchResearch PersonnelResolutionRetrievalScientistSecureServicesSiteSoftware FrameworkStandardizationTestingWorkbasebiomedical informaticsclinical carecomputer frameworkcomputerized toolscost effectivenessdata curationdata pipelinedata sharingdata toolsdeprivationdesigndigitalexperienceheterogenous dataimaging studyindexinginteroperabilityiterative designnovelopen sourceopen source libraryprecision medicineresearch studyspatiotemporalstatisticssustainability frameworksustainable resourcetooltool developmentuser-friendly
项目摘要
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.
项目概要
环境暴露和社区特征,包括空气污染、绿地、犯罪和指数
社区剥夺程度是健康的有力预测指标。这些数据被称为“地理标记”,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
前所未有的准入,为“精准医疗”扩展到“精准公共卫生”铺平了道路。
将这些新可用数据自动链接到现有研究和电子健康记录 (EHR) 数据库,
然而,由于时空分辨率和范围方面的数据异质性,通常很困难
化、存储、格式、检索方法和计算策略。这阻碍了数据的可访问性
互操作性。由于精确的地理定位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中的应用
由于获得适当的专业知识和依赖低效的手动数据管理,护理受到阻碍。我们批判地
缺少使可重复的地理标记评估能够广泛获取和易于使用的方法和工具
由生物医学研究人员。为了解决这一限制,我们的总体目标是开发一个精心策划的标准-
研究人员可以使用它来将地理标记与他们的研究结果进行高效、自动化和可重复的链接
拥有自己的数据和一个通用框架,暴露评估科学家可以为之做出贡献。我们将创造
基于软件容器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管道中进行测试实施,并获取反馈
来自用户和消费者。重要的是,该提案将为地理标记工具开发创建一个框架
这将允许任何用户以一致且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以及对我们的工具集的修改或添加。软-
软件、框架和容器库将免费且开源。我们的努力将使地理标记数据和
方法更容易找到、可访问、可互操作和可重用(公平),并且当我们寻求使我们的方法
一种广泛采用的、社区维护的、可持续的资源,以推动精准公共的进步
健康。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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{{ truncateString('Cole Brokamp', 18)}}的其他基金
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 - 财政年份:2020
- 资助金额:
$ 33.79万 - 项目类别:
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:
10221783 - 财政年份:2020
- 资助金额:
$ 33.79万 - 项目类别:
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