Collaborative Research: Frameworks: Building a Collaboration Infrastructure: CyberWater2 -- A Sustainable Data/Model Integration Framework

协作研究:框架:构建协作基础设施:Cyber​​Water2——可持续数据/模型集成框架

基本信息

  • 批准号:
    2209833
  • 负责人:
  • 金额:
    $ 108.27万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2023
  • 资助国家:
    美国
  • 起止时间:
    2023-01-01 至 2026-12-31
  • 项目状态:
    未结题

项目摘要

Natural hazards, such as coastal and inland flooding caused by Hurricanes and severe drought and its associated wildfire, have been occurring with unprecedented frequency, induced by climate changes that encompass hydrological, biological, environmental, atmospheric, ocean, and other geosciences. Such hazards have caused not only profound damages to our environment and required tremendous efforts to recover, but also cost people's lives. To mitigate these potential disasters, it is a critical time to tackle their associated scientific questions both fundamental and large-scale that impact on the health, resilience, and sustainability of the Earth system we live in. The problems are complex and multidisciplinary, and researchers and practitioners from diverse fields must work together to find solutions. By its nature, Earth system models are comprised of component models – from land surface, to rivers, coastal regions, ocean, sea ice, and atmosphere, where each component model is coupled with one another. As science advances, a component model or its subsystems may have to be replaced because of new understanding, or because different perspectives must be explored and tested for the credence of different combinations to find the most credible predictions for different conditions at different locations. Such tasks often require substantial efforts and time and can become a bottleneck. This project is aimed at developing a new open-source cyberinfrastructure framework, Cyberwater2, in which model coupling is shifted from the current "code-coupling" approach to a new "information coupling" approach, and can be configured without writing glue code. This minimizes the need to access and modify each participating model's original code, and removes a major obstacle for large-scale cross-institutional collaborations and scientific investigations across disciplines and geographic boundaries. CyberWater2 is designed for diverse research communities including water, climate, coastal, engineering, and beyond. With our framework, researchers can devote their collaborative energy on problem solving and exploration of new frontiers, while using CyberWater2 to effectively achieve two-way open model couplings across platforms, model parameter calibration, data assimilation, testing/validations/comparisons, etc.The goal of this project is to make it easier to conduct large scale collaboration on complex problems and solve them efficiently, accurately and in-depth by developing a cyberinfrastructure, CyberWatyer2, that (1) significantly eliminates "glue" coding for two-way couplings across heterogeneous computing platforms, disciplines, and organizations; (2) automates complex model calibration and facilitates data assimilation processes applicable to various models; (3) supports task-based and in-situ hybrid workflow for greatly improved efficiency on two-way coupling across heterogeneous platforms; (4) provides a CyberWater2 server and web service framework for users in addition to the standalone systems; (5) enables sustainable data access from diverse sources by automatically adapting data agents to the changes (e.g., API interfaces) made to external data sources by providers; and (6) enables automated resource planning with intelligent site recommendation for High Performance Computing (HPC)/Cloud access on demand to maximize users' benefits.This project is supported by the Office of Advanced Cyberinfrastructure in the Directorate for Computer & Information Science & Engineering and the Division of Earth Sciences in the Directorate of Geosciences.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.
自然灾害,如飓风造成的沿海和内陆洪水和严重干旱及其相关野火,以前所未有的频率发生,由气候变化引起,包括水文,生物,环境,大气,海洋和其他地球科学。这些灾害不仅对我们的环境造成了深刻的破坏,需要付出巨大的努力才能恢复,而且还使人们付出了生命的代价。为了减轻这些潜在的灾害,现在是解决与之相关的科学问题的关键时刻,这些问题既有根本性的,也有大规模的,它们会影响到我们生活的地球系统的健康、复原力和可持续性。这些问题是复杂和多学科的,来自不同领域的研究人员和从业人员必须共同努力找到解决办法。就其性质而言,地球系统模型由组件模型组成-从陆地表面到河流,沿海地区,海洋,海冰和大气,其中每个组件模型相互耦合。随着科学的进步,组件模型或其子系统可能必须被替换,因为新的理解,或者因为必须探索和测试不同组合的可信度以找到对不同位置的不同条件的最可信的预测。这些任务往往需要大量的努力和时间,并可能成为瓶颈。该项目旨在开发一个新的开源网络基础设施框架Cyberwater 2,其中模型耦合从当前的“代码耦合”方法转移到新的“信息耦合”方法,并且可以在不编写粘合代码的情况下进行配置。这最大限度地减少了访问和修改每个参与模型的原始代码的需要,并消除了跨学科和地理边界的大规模跨机构合作和科学研究的主要障碍。CyberWater 2专为水、气候、海岸、工程等不同的研究社区而设计。通过我们的框架,研究人员可以将他们的协作精力投入到解决问题和探索新的前沿领域,同时使用CyberWater 2有效地实现跨平台的双向开放模型耦合,模型参数校准,数据同化,测试/验证/比较等。该项目的目标是更容易地对复杂问题进行大规模协作并有效解决它们,通过开发网络基础设施CyberWatyer 2,准确和深入地:(1)大大消除了异构计算平台、学科和组织之间双向耦合的“胶水”编码;(2)自动化复杂的模型校准,促进适用于各种模型的数据同化过程;(3)支援以任务为基础的现场混合工作流程,大大提高跨异构平台双向耦合的效率;(4)除独立系统外,为用户提供CyberWater 2服务器和Web服务框架;(5)通过使数据代理自动适应变化(例如,API接口);以及(6)实现自动化资源规划,并根据需求为高性能计算(HPC)/云访问提供智能站点建议,以最大限度地提高用户的利益。该项目由计算机信息科学工程局高级网络基础设施办公室&&和地球科学局地球科学部支持。该奖项反映了NSF的法定基金会的使命是履行其使命,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价,被认为值得支持。

项目成果

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Xu Liang其他文献

A conceptual framework for mixing structures in individual aerosol particles
单个气溶胶颗粒混合结构的概念框架
  • DOI:
    10.1002/2016jd025252
  • 发表时间:
    2016-11
  • 期刊:
  • 影响因子:
    4.4
  • 作者:
    Li Weijun;Sun Jiaxing;Xu Liang;Shi Zongbo;Riemer Nicole;Sun Yele;Fu Pingqing;Zhang Jianchao;Lin Yangting;Wang Xinfeng;Shao Longyi;Chen Jianmin;Zhang Xiaoye;Wang Zifa;Wang Wenxing
  • 通讯作者:
    Wang Wenxing
Dual-comb based time-stretch optical coherence tomography for large and segmental imaging depth
基于双梳的时间拉伸光学相干断层扫描,用于大分段成像深度
  • DOI:
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    3.8
  • 作者:
    Xu Liang;Zhang Lei;Wang Kun;Liu Chen;Zhang Chi;Zhang Xinliang
  • 通讯作者:
    Zhang Xinliang
In Situ Observations of Light-Absorbing Carbonaceous Aerosols at Himalaya: Analysis of the South Asian Sources and Trans-Himalayan Valleys Transport Pathways
喜马拉雅地区吸光碳质气溶胶的现场观测:南亚来源和跨喜马拉雅山谷传输路径的分析
  • DOI:
    10.1029/2020jd032615
  • 发表时间:
    2020
  • 期刊:
  • 影响因子:
    4.4
  • 作者:
    Yuan Qi;Wan Xin;Cong Zhiyuan;Li Mengmeng;Liu Lei;Shu Shoujuan;Liu Rui;Xu Liang;Zhang Jian;Ding Xiaokun;Li Weijun
  • 通讯作者:
    Li Weijun
Parameters estimation of sinusoidal frequency modulation signal with application in synthetic aperture radar imaging
正弦调频信号参数估计及其在合成孔径雷达成像中的应用
  • DOI:
    10.1117/1.jrs.10.020502
  • 发表时间:
    2016-04
  • 期刊:
  • 影响因子:
    1.7
  • 作者:
    Wang Yong;Wang Zhaofa;Zhao Bin;Xu Liang
  • 通讯作者:
    Xu Liang
A Comprehensive Method for Subsidence Prediction on Two-Seam Longwall Mining
二煤层长壁开采沉陷综合预测方法
  • DOI:
    10.3390/en12163139
  • 发表时间:
    2019-08
  • 期刊:
  • 影响因子:
    3.2
  • 作者:
    Zhang Bin;Ye Jiacheng;Zhang Zhongjian;Xu Liang;Xu Nengxiong
  • 通讯作者:
    Xu Nengxiong

Xu Liang的其他文献

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{{ truncateString('Xu Liang', 18)}}的其他基金

Framework: Software: Collaborative Research: CyberWater--An open and sustainable framework for diverse data and model integration with provenance and access to HPC
框架:软件:协作研究:Cyber​​Water——一个开放且可持续的框架,用于将多种数据和模型集成,并提供 HPC 的来源和访问权限
  • 批准号:
    1835785
  • 财政年份:
    2019
  • 资助金额:
    $ 108.27万
  • 项目类别:
    Standard Grant
NeTS: Small: Collaborative Research: Compressed Network Tomography and Data Collection in Large-Scale Wireless Sensor Networking
NeTS:小型:协作研究:大规模无线传感器网络中的压缩网络断层扫描和数据收集
  • 批准号:
    1319331
  • 财政年份:
    2013
  • 资助金额:
    $ 108.27万
  • 项目类别:
    Standard Grant
Long-Term Solutions to Acid Producing Coal Mine Spoils Using Industrial Wastes
利用工业废物解决煤矿产酸弃渣问题的长期解决方案
  • 批准号:
    1236403
  • 财政年份:
    2012
  • 资助金额:
    $ 108.27万
  • 项目类别:
    Continuing Grant
Collaborative Research: From Data to Users: A Prototype Open Modeling Framework
协作研究:从数据到用户:原型开放建模框架
  • 批准号:
    1245067
  • 财政年份:
    2012
  • 资助金额:
    $ 108.27万
  • 项目类别:
    Standard Grant
EAGER: Collaborative Research: Network Inference and Data Collection Based on Compressed Sensing in Large-Scale Wireless Sensor Networking
EAGER:协作研究:大规模无线传感器网络中基于压缩感知的网络推理和数据收集
  • 批准号:
    1251995
  • 财政年份:
    2012
  • 资助金额:
    $ 108.27万
  • 项目类别:
    Standard Grant
NeTS-NOSS: Collaborative Research: Investigating Temporal Correlation for Energy Efficient and Lossless Communication in Wireless Sensor Networks
NetS-NOSS:协作研究:研究无线传感器网络中节能和无损通信的时间相关性
  • 批准号:
    0721474
  • 财政年份:
    2007
  • 资助金额:
    $ 108.27万
  • 项目类别:
    Continuing Grant

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