Columbia Population Research Center - Computing and Methods Core

哥伦比亚人口研究中心 - 计算和方法核心

• 批准号: 10597032
• 负责人: Julien O Teitler
• 金额: $ 7.89万
• 依托单位: COLUMBIA UNIV NEW YORK MORNINGSIDE
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-08-15 至 2025-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10597032
• 关键词: Address; Adoption; Applications Grants; Collaborations; Computer Systems; Computer software; Consultations; Data; Data Analyses; Data Collection; Data Science; Data Storage and Retrieval; Development; Economics; Educational workshop; Elements; Environment; Equipment; Faculty; Fostering; Foundations; Funding; Generations; Geography; High Performance Computing; Information Technology; Infrastructure; Institution; Interview; Longitudinal Surveys; Manuscripts; Maps; Methodology; Methods; Neighborhoods; New York City; Personal Satisfaction; Play; Policies; Population Research; Poverty; Preparation; Price; Probability Samples; Productivity; Protocols documentation; Qualifying; Research; Research Design; Research Methodology; Research Personnel; Resources; Robin bird; Scholarship; Schools; Scientist; Secure; Services; Social Sciences; Social Work; Study Subject; Surveys; System; Technical Expertise; Training; Universities; Visualization; Work; astrophysics; cluster computing; computer infrastructure; cost; data enclave; design; experience; falls; field study; field survey; human subject; improved; innovation; member; repaired; scale up; social; social science research; statistics; symposium; tool; virtual; web site

Abstract – Computing and Methods Core The computing and methods core (CMC) achieves CPRC aims by providing a variety of computing and methods services that are designed to increase the productivity, efficiency, and quality of CPRC scholarship. These services, which have transformed the computing and methods infrastructure at Columbia, include: 1) Cross-Institutional Collaboration. The CMC plays a key role in building collaborations with other campus units that have resulted in major improvements in the university's IT infrastructure in high performance computing (HPC), facilities for the analysis of sensitive and restricted data, wrap-around desktop support services, and a shared research data storage initiative. 2) High Performance Computing (HPC). The CMC's initiation of a HPC cluster greatly advanced the state of HPC to meet the needs of population research at Columbia. Currently 23 CPRC affiliates have accounts on the HPC system. 3) Secure Computing Environment. The CMC established a Secure Data Enclave (SDE) service for CPRC and its partners in fall 2012. The SDE is a virtual computing environment that provides secure remote access to restricted data and statistical applications. The CMC co-chairs have worked with the Columbia University Informational Technology (CUIT) office to scale up the SDE, increasing its storage capacity and computational power. 4) Desktop Support. The CMC continues to provide wrap-around desktop support for its members. 5) GIS Services. The GIS consulting service includes support for study design and grant application preparation, advice on the analysis of spatial and neighborhood data, and the development of maps and visualizations for scientific manuscripts, seminars, and websites. 6) Support for Innovative Methodologies. A priority of the CMC moving forward is to promote the adoption of data science innovations among its faculty, through conferences demonstrating the value of new data collection and analysis tools, training workshops, and facilitating collaborations with data science scholars. Collaborations with Columbia's Data Science Institute are already very active. 7) Survey Lab. The Robin Hood Foundation funds the New York City Longitudinal Survey of Wellbeing (NYCLSW, aka “Poverty Tracker”), an ongoing panel study of New Yorkers, interviewed every 3 months. To accommodate the growing need for space for survey staff to conduct interviews, CPRC partnered with the School of Social Work to open the CPRC survey lab in 2017. The survey lab staff and management can be deployed by CPRC faculty to field surveys or for survey research consultations. The NYCLSW is also available to field test questions and collect experimental data on a probability sample of New Yorkers at very low costs.

摘要-计算和方法核心 计算和方法核心（CMC）通过提供各种计算和方法来实现CPRC的目标 旨在提高生产力，效率和CPRC奖学金质量的服务。这些 这些服务改变了哥伦比亚的计算和方法基础设施，包括： 1)跨机构合作。CMC在与其他校园建立合作方面发挥着关键作用 这些单位在大学的IT基础设施方面取得了重大改进， 计算（HPC）、用于分析敏感和受限数据的设施、环绕式桌面支持 服务和共享研究数据存储计划。 2)高性能计算（HPC）。CMC发起的HPC集群极大地推进了 HPC以满足哥伦比亚人口研究的需要。目前有23个CPRC附属机构在 高性能计算系统。 3)安全计算环境。CMC为CPRC建立了一个安全数据飞地（Secure Data Enclave）服务， 2012年秋季的合作伙伴。虚拟机是一个虚拟计算环境，它提供安全的远程访问， 限制数据和统计应用。CMC联合主席与哥伦比亚大学合作 信息技术（CUIT）办公室，以扩大数据库，增加其存储容量和计算能力 动力. 4)桌面支持。CMC继续为其成员提供环绕式桌面支持。 5)GIS服务。GIS咨询服务包括研究设计和拨款申请支持 准备，就空间和邻里数据的分析提供咨询，以及地图的开发， 科学手稿、研讨会和网站的可视化。 6)支持创新方法。CMC前进的一个优先事项是促进通过 通过会议展示新数据收集的价值，在其教师中进行数据科学创新 和分析工具，培训研讨会，并促进与数据科学学者的合作。 与哥伦比亚数据科学研究所的合作已经非常活跃。 7)测量实验室罗宾汉基金会资助纽约市幸福纵向调查 （NYCLSW，又名“贫困追踪者”），一个正在进行的纽约人小组研究，每3个月采访一次。到 为了满足调查人员进行访谈对空间日益增长的需求，CPRC与 社会工作学院将于2017年开设CPRC调查实验室。测量实验室工作人员和管理人员可以 由CPRC教师部署到实地调查或调查研究咨询。NYCLSW还提供 以极低的成本对纽约人的概率样本进行实地测试并收集实验数据。