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:CyberWater——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
基本信息
- 批准号:1835817
- 负责人:
- 金额:$ 51.42万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2019
- 资助国家:美国
- 起止时间:2019-01-01 至 2023-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
This project addresses a high priority need for water research communities: interoperability among a wide variety of data sources and models, and integration of different computational models into water research communities. The project will develop an open and sustainable software framework enabling integration of hydrologic data and models for interdisciplinary teamwork and discovery. The models and datasets cover fields such as hydrology, biology, environmental engineering and climate. The project also addresses one of the key issues for extreme-scale computing: scalable file systems. The collaboration draws upon computing, modeling, and hydrology expertise at six institutions: University of Pittsburgh, University of Iowa, Ball State University, North Carolina State University, Indiana University, and the Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI). The project develops CyberWater, a community-driven software framework that integrates a wide range of models and datasets across disparate temporal and spatial scales. The CyberWater framework allows scientists to bypass challenges associated with model and dataset complexity. The project designs a model agent tool enabling users to generate model agents for common model types without coding, and integrates multiple existing software codes/elements that provide for broad-scale use. To develop such a diverse modeling framework, the project brings together hydrologists, climate experts, meteorologists, computer scientists and cyberinfrastructure experts. The project builds upon an existing prototype developed by the lead investigator; basic elements for the system were developed, consisting of plugged-in models and data sources with corresponding agents and a workflow engine allowing user workflow control. The prototype was successfully demonstrated for two models, making use of datasets plugged in from NASA, USGS and CUAHSI. For the current project, new models and datasets are added to the framework; the ability to use high performance computing resources is also incorporated. The team will use the CUAHSI HydroShare System to distribute CyberWater software and its associate model agents, including instructions on how to establish a local CyberWater environment, models and model agents. The project will enable substantial scientific advances for water related issues, and the solution can be applied to other research disciplines. This award by the Office of Advanced Cyberinfrastructure is jointly supported by the NSF Directorate for 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.
该项目解决了水研究界的高度优先需求:各种数据源和模型之间的互操作性,以及将不同的计算模型集成到水研究界。 该项目将开发一个开放和可持续的软件框架,使水文数据和模型的整合,跨学科的团队合作和发现。 这些模型和数据集涵盖水文学、生物学、环境工程和气候等领域。 该项目还解决了极端规模计算的关键问题之一:可伸缩文件系统。 这项合作利用了六个机构的计算、建模和水文专业知识:匹兹堡大学、爱荷华州大学、鲍尔州立大学、北卡罗来纳州州立大学、印第安纳州大学和水文科学促进大学联盟。(CUAHSI)。 该项目开发了CyberWater,这是一个社区驱动的软件框架,集成了跨不同时空尺度的各种模型和数据集。CyberWater框架允许科学家绕过与模型和数据集复杂性相关的挑战。 该项目设计了一个模型代理工具,使用户能够生成通用模型类型的模型代理,而无需编码,并集成了多个现有的软件代码/元素,提供广泛的使用。 为了开发这样一个多样化的建模框架,该项目汇集了水文学家,气候专家,气象学家,计算机科学家和网络基础设施专家。 该项目以首席调查员开发的现有原型为基础;开发了该系统的基本要素,包括插入式模型和数据源,以及相应的代理和允许用户控制工作流程的工作流程引擎。 该原型成功地为两个模型进行了演示,利用了NASA,USGS和CUAHSI的数据集。 对于当前的项目,新的模型和数据集被添加到框架中;使用高性能计算资源的能力也被纳入其中。 该团队将使用CUAHSI HydroShare系统分发CyberWater软件及其相关模型代理,包括如何建立本地CyberWater环境、模型和模型代理的说明。该项目将使与水有关的问题取得实质性的科学进展,该解决方案可应用于其他研究学科。该奖项由高级网络基础设施办公室颁发,并得到NSF地球科学理事会的共同支持。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
期刊论文数量(5)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Accelerating complex modeling workflows in CyberWater using on-demand HPC/Cloud resources
使用按需 HPC/云资源加速 CyberWater 中的复杂建模工作流程
- DOI:10.1109/escience51609.2021.00030
- 发表时间:2021
- 期刊:
- 影响因子:0
- 作者:Li, Feng;Chen, Ranran;Fu, Yuankun;Song, Fengguang;Liang, Yao;Ranawaka, Isuru;Pamidighantam, Sudhakar;Luna, Daniel;Liang, Xu
- 通讯作者:Liang, Xu
CyberWater: An Open Framework for Data and Model Integration in Water Science and Engineering
CyberWater:水科学与工程中数据和模型集成的开放框架
- DOI:10.1145/3511808.3557186
- 发表时间:2022
- 期刊:
- 影响因子:0
- 作者:Chen, Ranran;Luna, Daniel;Li, Feng;Young, Ryan;Bieger, Drew;Song, Fengguang;Pamidighantam, Sudhakar;Liang, Yao;Liang, Xu
- 通讯作者:Liang, Xu
X-composer: enabling cross-environments in-situ workflows between HPC and cloud
X-composer:支持 HPC 和云之间的跨环境现场工作流程
- DOI:10.1145/3468267.3470621
- 发表时间:2021
- 期刊:
- 影响因子:0
- 作者:Li, Feng;Wang, Dali;Yan, Feng;Song, Fengguang
- 通讯作者:Song, Fengguang
Open data and model integration through generic model agent toolkit in CyberWater framework
- DOI:10.1016/j.envsoft.2022.105384
- 发表时间:2022-03
- 期刊:
- 影响因子:0
- 作者:Ranran Chen;Daniel Luna;Yuan Cao;Yao Liang;Xu Liang
- 通讯作者:Ranran Chen;Daniel Luna;Yuan Cao;Yao Liang;Xu Liang
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Yao Liang其他文献
Selection of chemotherapy for older patients with pancreatic cancer based on geriatric assessment.
根据老年评估选择老年胰腺癌患者的化疗方案。
- DOI:
10.1016/j.jgo.2022.09.005 - 发表时间:
2022 - 期刊:
- 影响因子:3
- 作者:
O. Maeda;A. Matsuoka;Madoka Yanagawa;Y. Muroyama;Kazuhisa Watanabe;Yao Liang;T. Ishikawa;E. Ohno;H. Kawashima;H. Umegaki;M. Kuzuya;Y. Ando - 通讯作者:
Y. Ando
Effect of Al on Microstructure and Properties of Hot-Rolled 2205 Dual Stainless Steel
Al对热轧2205双不锈钢组织和性能的影响
- DOI:
10.1155/2016/7518067 - 发表时间:
2016-07 - 期刊:
- 影响因子:0
- 作者:
Meng Qian;La Peiqing;Yao Liang;Zhang Peng;Wei Yupeng;Guo Xin - 通讯作者:
Guo Xin
Real-time multi-view vision systems using WSNs
使用 WSN 的实时多视图视觉系统
- DOI:
10.1145/1529282.1529765 - 发表时间:
2009 - 期刊:
- 影响因子:0
- 作者:
P. Pagano;Francesco Piga;Yao Liang - 通讯作者:
Yao Liang
Wireless line sensor network for distributed visual surveillance
用于分布式视觉监控的无线线路传感器网络
- DOI:
10.1145/1641876.1641890 - 发表时间:
2009 - 期刊:
- 影响因子:20.6
- 作者:
M. Chitnis;Yao Liang;J. Zheng;P. Pagano;Giuseppe Lipari - 通讯作者:
Giuseppe Lipari
Utilisation of sodium oleate/alkylamide collectors for the selective separation of fluorite and calcite
- DOI:
10.1016/j.molliq.2024.125925 - 发表时间:
2024-11-01 - 期刊:
- 影响因子:
- 作者:
Wenxia Zhu;Jianhua Kang;Danxian Zhang;Yangge Zhu;Jie Ding;Yao Liang;Haisheng Han;Wei Sun;Zhiyong Gao - 通讯作者:
Zhiyong Gao
Yao Liang的其他文献
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{{ truncateString('Yao Liang', 18)}}的其他基金
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:CyberWater2——可持续数据/模型集成框架
- 批准号:
2209835 - 财政年份:2023
- 资助金额:
$ 51.42万 - 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:
1320132 - 财政年份:2013
- 资助金额:
$ 51.42万 - 项目类别:
Standard 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:
1245171 - 财政年份:2012
- 资助金额:
$ 51.42万 - 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:
1252066 - 财政年份:2012
- 资助金额:
$ 51.42万 - 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:
0758372 - 财政年份:2007
- 资助金额:
$ 51.42万 - 项目类别:
Continuing 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:
0721853 - 财政年份:2007
- 资助金额:
$ 51.42万 - 项目类别:
Continuing Grant
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