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Data Repository and Management Core

数据存储和管理核心

基本信息

批准号：
10006827
负责人：
Patricia Kovatch
金额：
$ 108.66万
依托单位：
ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
依托单位国家：
美国
项目类别：
财政年份：
资助国家：
美国
起止时间：
至
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10006827
关键词：
Address Big Data Child Health Collection Communities Computer software Data Data Aggregation Data Analyses Data Analytics Data Science Data Set Deposition Descriptor Documentation Economic Models Eligibility Determination Ensure Environmental Exposure Environmental Health FAIR principles Future General Population Generations Guidelines Health Health Insurance Portability and Accountability Act Human Individual Infrastructure Ingestion Intuition Laboratories Life Metadata Modernization Policies Procedures Process Productivity Reporting Reproducibility Research Research Personnel Resources Retrieval Role Sample Size Scientific Advances and Accomplishments Secure Security Self-Direction Semantics Services Sum Time Training United States National Institutes of Health Visualization software Vocabulary Work analytical method analytical tool data access data centers data harmonization data integrity data management data portal data resource data reuse data sharing data standards data submission data visualization data warehouse design experience flexibility genome wide association study interoperability large datasets metabolomics multimodal data programs quality assurance query tools social media study population tool user-friendly webinar

项目摘要

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.

数据存储和管理核心项目汇总