Framework: Sofware: 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，用于将各种数据和模型集成到 HPC 的来源和访问权限

• 批准号: 1835656
• 负责人: Yang Zhang
• 金额: $ 9.5万
• 依托单位: North Carolina State University
• 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 2020-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1835656&HistoricalAwards=false
• 关键词: Framework; Sofware; Collaborative; Research; CyberWater

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.

该项目解决了对水研究社区的高优先级需求：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社区中。 该项目将开发一个开放且可持续的软件框架，从而可以将水文数据和模型集成用于跨学科的团队合作和发现。 模型和数据集涵盖水文学，生物学，环境工程和气候等领域。 该项目还解决了极限计算的关键问题之一：可扩展文件系统。 合作借鉴了六个机构的计算，建模和水文专业知识：匹兹堡大学，爱荷华大学，鲍尔州立大学，北卡罗来纳州立大学，印第安纳大学，以及水平科学促进的大学财团（CUAHSI）。 该项目开发网络水域，这是一个社区驱动的软件框架，该框架在不同的时间和空间尺度上集成了广泛的模型和数据集。网络水框架允许科学家绕过与模型和数据集复杂性相关的挑战。 该项目设计一种模型代理工具，使用户能够在不编码的情况下为通用模型类型生成模型代理，并集成了提供广泛使用的多个现有软件代码/元素。 为了开发如此多样化的建模框架，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。 该项目建立在主要研究人员开发的现有原型上； 开发了系统的基本元素，由带有相应代理的插入模型和数据源组成，以及允许用户工作流控制的工作流引擎。 该原型已成功地用于两个模型，利用了NASA，USGS和Cuahsi插入的数据集。 对于当前项目，将新的模型和数据集添加到框架中；还结合了使用高性能计算资源的能力。 该团队将使用Cuahsi水力发电系统来分发网络水软件及其副模型代理，包括有关如何建立本地网络水域环境，模型和模型代理的说明。该项目将使与水有关的问题实现大量科学进步，并且该解决方案可以应用于其他研究学科。 NSF地理科学局共同支持高级网络基础设施办公室的奖项。该奖项反映了NSF的法定任务，并使用基金会的知识分子优点和更广泛的影响审查标准，认为值得通过评估值得支持。