Data Repository and Management Core
Data Repository and Management Core
批准号:
10684793
负责人:
Patricia Kovatch
金额:
$91.47万
依托单位国家:
美国
项目类别:
财政年份:
2015
资助国家:
美国
项目状态:
已结题
起止时间:
2015-09-30 至 2024-05-31
关键词:
AccelerationAddressBig DataChild HealthCollaborationsCollectionCommunitiesComputer softwareDataData AggregationData AnalysesData AnalyticsData ScienceData SetDepositionDescriptorDocumentationEconomic ModelsEligibility DeterminationEnsureEnvironmental ExposureEnvironmental HealthFAIR principlesFutureGeneral PopulationGenerationsGuidelinesHealthHealth Insurance Portability and Accountability ActHumanIndividualInfrastructureIngestionIntuitionLaboratoriesLifeLife Cycle StagesMapsMetadataModernizationPoliciesProceduresProcessProductivityReportingReproducibilityResearchResearch PersonnelResourcesRetrievalRoleSample SizeScientific Advances and AccomplishmentsSecureSecuritySelf DirectionSemanticsServicesTrainingUnited States National Institutes of HealthVisualization softwareVocabularyWorkanalytical methodanalytical tooldata accessdata centersdata harmonizationdata integritydata managementdata portaldata repositorydata resourcedata reusedata sharingdata standardsdata submissiondata visualizationdesignexperiencefederated dataflexibilitygenome wide association studyimplementation processinteroperabilitylarge datasetsmetabolomicsmultimodal dataprogramsquality assurancequery toolssocial mediastudy populationtoolusabilityuser-friendlywebinar
中文摘要
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英文摘要
DATA REPOSITORY AND MANAGEMENT CORE PROJECT SUMMARY
The Data Repository and Management Core (DRMC) will advance scientific understanding of environmental
exposures by expanding our successful CHEAR Data Center (DC) data portal and repository to encompass
humans at all life stages. Our proposed HHEAR DC data portal and repository, along with our effective user
support team, will help researchers add comprehensive exposure analysis to their studies. Our demonstrated
commitment to FAIR principles and our unique harmonized data sets will enhance research productivity and
general public understanding by (1) providing access to cleaned and harmonized data and larger data sets for
greater statistical power and maximal reuse; (2) interoperating with relevant national data sets such as the
Metabolomics Workbench, ECHO, and others to facilitate data submission of new data types; and (3)
facilitating access to modern collaborative data analysis tools such as Jupyter notebooks and Google's
Colaboratory. We will employ best practices for high reliability and security and follow HIPAA guidelines. To
develop effective and focused infrastructure, services, and processes tailored for the CHEAR community, our
interdisciplinary team developed strong partnerships with the Coordinating Center (CC), the Lab Network, the
ECHO DC, the Metabolomics Workbench, and others. These relationships, along with our existing CHEAR
infrastructure, singular expertise, and established processes, will carry over to the creation of the HHEAR DC
and will help accelerate its rollout. These services will give the HHEAR community the ability to discover new
correlations and relationships between multi-scale and multimodal data sets, thus progressing toward the
promise of big data to help solve the major challenges of human environmental health research across the
lifecourse. Combining data from a set of individual studies would likely require substantial work if it were
attempted without resources similar to those of the HHEAR DMRC; the design of the data repository will
facilitate manageable and efficient combining of existing data sets; the availability of common vocabularies
developed by the DSR will contribute to maximizing the usable data from each study; and the SSAR will
ultimately receive a dataset to which they can apply their exposome-related analytic methods to address
hypotheses on the environmental health of the pooled study population. Our state-of-the-art DRMC has been
fulfilling these roles within the CHEAR program, and will build on and extend our capabilities as the HHEAR
DC. In sum, leveraging our existing infrastructure and expertise will overcome the need for a long
implementation process fraught with challenges — we have already encountered and overcome many such
challenges in implementing the CHEAR DC, and will be able to flexibly respond to the needs of HHEAR
Network.
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COVID and Translational Science supercomputer (CATS)
-
批准号:10177277
-
项目类别:
-
资助金额:$200.0万
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财政年份:2021
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负责人:Patricia Kovatch
-
依托单位:
Data Repository and Management Core
-
批准号:10424417
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项目类别:
-
资助金额:$79.5万
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财政年份:2015
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负责人:Patricia Kovatch
-
依托单位:
Transforming Genomics with 5 PB Big Omics Data Engine Cray CS300-AC Supercomputer
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批准号:8734830
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项目类别:
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资助金额:$194.7万
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财政年份:2014
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负责人:Patricia Kovatch
-
依托单位:
Data Repository and Management Core
-
批准号:10006827
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项目类别:
-
资助金额:$108.66万
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财政年份:--
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负责人:Patricia Kovatch
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依托单位:
Data Repository and Management Core
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批准号:9814207
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项目类别:
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资助金额:$77.06万
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财政年份:--
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负责人:Patricia Kovatch
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依托单位:
海外基金