Science Core

科学核心摘要-科学核心（SC）的目的是提供学者附属于杜克 人口研究中心（DPRC）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。在过去的五年里，DPRC（1） 投资于SC服务，利用杜克丰富的IT基础设施，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， 模拟工具，（2）有助于确定对复杂人口分析的适当技术支持，以及（3） 提供了新技术培训，包括分析“大”数据源的技术，如基于网络的数据。在 未来五年，安全理事会将：（1）继续为国防研究中心提供并保持良好的计算资源 学者，和（2）开发可访问和可复制的工具，方法和专业知识，用于编译，策展， 链接和分析不断增长的人口“大型”行政和医疗数据 研究，DPRC学者已经参与该领域，但在使用时仍面临重大挑战 他们为了实现后一个目标，DPRC将汇集杜克的学者与当地的合作伙伴关系， 政府机构和地区机构建立达勒姆人口实验室（DPL），这一倡议将 允许检查有助于不同健康轨迹的社会和环境特征， 种族和民族多样化的人口。DPL将作为一个测试“厨房”，纳入新的数据， 方法，利用大的人口规模进行非随机抽样推断，并为 快速评估以证据为基础的政策制定，同时推进NICDH人口动态 分支的总体兴趣是为“大”人口和健康科学开发新工具和技术。

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.