Science Core

科学核心

基本信息

批准号：
10583475
负责人：
Marcos de Almeida Rangel
金额：
$ 9.84万
依托单位：
DUKE UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2010
资助国家：
美国
起止时间：
2010-08-01 至 2025-02-28
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10583475
关键词：
Acceleration Address Adopted Archives Area Big Data Bioinformatics Code Cohort Studies Complex Computer software Country County Data Data Analyses Data Analytics Data Collection Data Protection Data Sources Development Ensure Environment Ethics Face Faculty Funding Goals Government Agencies Growth Health Health Sciences Healthcare Information Systems Information Technology Infrastructure Institution Institutional Review Boards Internet Intervention Investments Legal Link Local Government Location Methods Modeling North Carolina Online Systems Personal Satisfaction Policies Policy Making Population Population Analysis Population Dynamics Population Heterogeneity Population Research Population Sciences Population Sizes Privatization Procedures Protocols documentation Records Reproducibility Research Research Institute Research Personnel Research Support Resources Sampling Science Secure Security Services Site Students Techniques Technology Testing Time Training United States National Institutes of Health Universities Vendor Vertebral column Work analytical tool complex data computer infrastructure computing resources cost effective data access data infrastructure data integration data management design digital econometrics ethnic diversity evidence base flexibility improved innovation interest new technology novel strategies online resource population health programs racial diversity simulation social social science research synergism task analysis tool

项目摘要

Science Core Abstract -- The Science Core (SC) is designed to provide scholars affiliated with the Duke Population Research Center (DPRC) with high quality, flexible computing and technical services in a cost- effective manner; including both data access and analytic tools. Over the past five years DPRC has (1) invested in SC services that leverage the rich IT infrastructure at Duke to ensure provision and seamless access to computational resources, new analysis tools, support for high-intensity network sampling and simulation tools, (2) helped to identify appropriate technical support for complex population analysis, and (3) provided training in new techniques, including those to analyze “big” data sources such as web-based data. In the next five years, the SC will: (1) build on and maintain excellent computational resource provision for DPRC scholars, and (2) develop accessible and reproducible tools, methods, and expertise for compiling, curating, linking, and analyzing an ever growing volume of “big” administrative and healthcare data for population research, an area in which DPRC scholars are already involved but still face significant challenges to use them. To accomplish the latter goal, DPRC will bring together scholars at Duke in partnerships with local government agencies and regional institutions to build the Durham Population Lab (DPL), an initiative that will permit the examination of social and environmental features that contribute to divergent health trajectories in a racially and ethnically diverse population. The DPL will function as a test “kitchen,” incorporating new data and approaches, leveraging large population size for non-random sampling inference, and provide opportunities for rapid assessment for evidence-based policy making, while advancing the NICDH Population Dynamics Branch’s general interests in developing new tools and techniques for “big” population and health science.

科学核心摘要——科学核心（SC）旨在为杜克大学附属学者提供人口研究中心（DPRC）以低成本提供高质量、灵活的计算和技术服务有效的方式；包括数据访问和分析工具在过去五年中，DPRC (1) 投资于 SC 服务，利用杜克大学丰富的 IT 基础设施来确保供应和无缝访问计算资源、新的分析工具、支持高强度网络采样和模拟工具，(2) 帮助确定复杂群体分析的适当技术支持，以及 (3) 提供新技术培训，包括分析“大”数据源（例如基于网络的数据）的培训。未来五年，SC 将：(1) 建立并维持为 DPRC 提供的优秀计算资源学者们，以及（2）开发可获取和可复制的工具、方法和专业知识，用于编译、策划、链接和分析数量不断增长的人口“大”行政和医疗保健数据研究，DPRC 学者已经涉足这一领域，但在使用方面仍面临重大挑战为了实现后一个目标，DPRC 将汇集杜克大学的学者与当地合作伙伴。政府机构和地区机构建立达勒姆人口实验室（DPL），这一举措将允许检查导致不同健康轨迹的社会和环境特征 DPL 将充当测试“厨房”，纳入新的数据和数据。方法，利用大量人口进行非随机抽样推断，并提供机会快速评估循证决策，同时推进 NICDH 人口动态布兰奇对为“大”人口和健康科学开发新工具和技术的总体兴趣。