Computing and Methods Core

计算和方法核心

• 批准号: 8846277
• 负责人: Julien O Teitler
• 金额: $ 6.79万
• 依托单位: COLUMBIA UNIV NEW YORK MORNINGSIDE
• 依托单位国家: 美国
• 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/8846277
• 关键词: Accounting; Address; Applications Grants; Archives; Big Data; Budgets; Censuses; Collaborations; Computer software; Confidentiality; Consult; Consultations; Cost Savings; Cost Sharing; Data; Data Analyses; Data Storage and Retrieval; Development; Development Plans; Educational workshop; Environment; Equipment; Faculty; Foundations; Funding; Genetic; High Performance Computing; Housing; Imagery; Journals; Longitudinal Surveys; Manuscripts; Maps; Methodology; Methods; National Institute of Child Health and Human Development; Neighborhoods; New York; New York City; Paper; Peer Review; Personal Satisfaction; Play; Policies; Population Research; Population Sciences; Preparation; Price; Productivity; Protocols documentation; Publishing; Research; Research Design; Research Infrastructure; Research Personnel; Robin bird; Sampling; Scholarship; Secure; Services; Social Sciences; Study Subject; Surveys; System; Testing; Training Support; Universities; Work; abstracting; cloud based; data sharing; design; discount; experience; falls; human subject; meetings; member; repaired; social science research; symposium; tool development; virtual; web site

Abstract  Computing and Methods Core The Computing and Methods Core (CMC) contributes to achieving CPRC specific 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 include: 1) Cross-Institutional Collaboration. The CMC, along with the Administrative Core, plays a key role in constructing collaborations with other campus units that has resulted in major improvements in the University's IT infrastructure in High Performance Computing, 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 state of high performance computing that meets the needs of population research at Columbia was greatly advanced with the CMC's initiation of a high performance computing cluster in 2011. In the two years since Hotfoot was launched, 29 CPRC affiliates have opened accounts and 11 articles from studies that relied on Hotfoot were published in peer-reviewed journals. 3) Secure Computing Environment. The CMC established a Secure Data Enclave (SDE) service for the 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. 4) Desktop Support. The CMC now provides wrap-around desktop support for its members. 5) Data Storage. In collaboration with CUIT, SSCC, and Columbia's Shared Research Computing Advisory Policy Committee (SRCPAC), the CPRC's CMC has developed an in-house platform for data sharing and analysis, which is more versatile and provides a more secure environment than cloud-based data storage. 6) 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. 7) Methodological Consultation. The co-directors of the CMC connect researchers, including junior faculty, in need of methodological consultation with CPRC faculty who have the relevant expertise. 8) Methodology Workshops. The CPRC has held five methodological workshops. Two new methodology conferences are being planned: one in 2015 on Methodological Issues in the Study of Genetics and Population Science and one in 2016 on Big Data. Both will promote the application of new methods to population science. 9) Robin Hood Survey Lab. The Robin Hood funded New York City Longitudinal Survey of Well-being is an ongoing panel study of New Yorkers that includes an experimental sample allowing CPRC investigators to test questions and survey research approaches.

摘要计算与方法核心