Unidata: Next-generation Data Services and Workflows to Advance Geoscience Research and Education

Unidata：推动地球科学研究和教育的下一代数据服务和工作流程

• 批准号: 1901712
• 负责人: Mohan Ramamurthy
• 金额: $ 2150万
• 依托单位: University Corporation For Atmospheric Res
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-05-01 至 2024-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1901712&HistoricalAwards=false
• 关键词: Unidata; Next; generation; Data; Services

Unidata is a community data facility for the atmospheric and related sciences, established in 1984 by U.S. universities with sponsorship from the National Science Foundation. Unidata's goal is to help transform the conduct of research and education in the atmospheric and related sciences by providing well integrated data services and tools that address the entire scientific data lifecycle, from locating and retrieving useful data, through the process of analyzing and visualizing data either locally or remotely, to curating and sharing the results. Unidata serves more than five thousand of educational, government, and research institutions that rely on Unidata technologies worldwide.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Unidata是一个大气和相关科学的社区数据设施，由美国大学在国家科学基金会的赞助下于1984年建立。 Unidata的目标是通过提供良好集成的数据服务和工具来帮助改变大气和相关科学的研究和教育行为，这些服务和工具可以解决整个科学数据生命周期，从定位和检索有用的数据，通过本地或远程分析和可视化数据的过程，到管理和共享结果。 Unidata为全球5000多家依赖Unidata技术的教育、政府和研究机构提供服务。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Introducing Students to Scientific Python for Atmospheric Science

向学生介绍用于大气科学的科学 Python

• DOI: 10.1175/bams-d-20-0069.1
• 发表时间: 2020
• 期刊: Bulletin of the American Meteorological Society
• 影响因子: 8
• 作者: Arms, Sean;Chastang, Julien;Grover, Maxwell;Thielen, Jon;Wilson, Matthew;Dirks, Douglas
• 通讯作者: Dirks, Douglas

Data Interoperability Between Elements of the Global Ocean Observing System

全球海洋观测系统各要素之间的数据互操作性

• DOI: 10.3389/fmars.2019.00442
• 发表时间: 2019
• 期刊: Frontiers in Marine Science
• 影响因子: 3.7
• 作者: Snowden, Derrick;Tsontos, Vardis M.;Handegard, Nils Olav;Zarate, Marcos;O’ Brien, Kevin;Casey, Kenneth S.;Smith, Neville;Sagen, Helge;Bailey, Kathleen;Lewis, Mirtha N.
• 通讯作者: Lewis, Mirtha N.

High-performance reliable network-multicast over a trial deployment

• DOI: 10.1007/s10586-021-03519-6
• 发表时间: 2022-02
• 期刊: Cluster Computing
• 作者: Yuanlong Tan;M. Veeraraghavan;Hwajung Lee;S. Emmerson;J. Davidson

The Experimental Warning Program of NOAA’s Hazardous Weather Testbed

NOAA 危险天气试验台的实验预警计划

• DOI: 10.1175/bams-d-21-0017.1
• 发表时间: 2021
• 期刊: Bulletin of the American Meteorological Society
• 影响因子: 8
• 作者: Meyer, Tiffany;Krocak, Makenzie J.;Smith, Travis M.;Stumpf, Greg;Gerard, Alan
• 通讯作者: Gerard, Alan