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
• 负责人: Yao Liang
• 金额: $ 8.85万
• 依托单位: Indiana University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-07-15 至 2014-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1245171&HistoricalAwards=false
• 关键词: Collaborative; Research; Data; Users; Prototype; Collaborative; Research; Data; Users; Prototype

Because Earth is a complex coupled interacting system, where no one element is independent of any other, there are both pressing scientific and societal needs to improve our understanding how various physical, biological, and hydrological processes interact in surface Earth systems. This requires the development of new and increasingly more sophisticated ways of mathematically describing these systems and improvements in software and user interfaces that will dramatically enhance our ability to simulate these systems to improve the accuracy and reliability of model predictions of weather, floods, droughts, and climate variability. Such improved models will allow researchers to make better use of available data across disciplines and improve theory and algorithms that are essential to understanding Earth system behavior. Unfortunately, at present there is significant overhead of time and effort needed for discovering, accessing, understanding, and preparing data required to populate these models, as well as long learning lead times on how to use presently available models, owing to their complexity. This research overcomes some of these limitations by developing an innovative open modeling framework that can integrate data and models easily and is easy to use so that not only the research community and operational professionals can use it, but also policy makers and other interested parties. This EAGER award allows the construction of a prototype open meta-modeling framework that significantly reduces the time and effort on the part of users in the preparatory work for data and model comparisons, model testing and validations, for making fundamental knowledge discoveries in surface and ground water hydrological systems. In this framework, components/modules interact via user-configured open interfaces that allow the addition and integration of hydrological models and data sources using a common meta-level architecture and scientific workflows. The proposed prototype is based on a recently completed modeling framework, HS-NWSRFS (Hydro-information System for improving the National Weather Service River Forecast System). It represents a collaboration between investigators from three institutions, NASA, and NWS Ohio River Forecast Center (OHRFC). The funded effort will significantly expand the present code into an open community framework prototype. Broader impacts of the work include interagency collaboration, improved hydrological forecasting for rivers, and support of a PI whose gender is under-represented in the sciences.

由于地球是一个复杂的耦合相互作用系统，没有任何一个元素独立于其他元素，因此有紧迫的科学和社会需要提高我们的理解，我们了解各种物理，生物学和水文过程如何在表面地球系统中相互作用。 这就需要开发新的，越来越复杂的方式来数学描述这些系统以及软件和用户界面的改进，这将极大地增强我们模拟这些系统的能力，以提高天气，洪水，干旱和气候变化的模型预测的准确性和可靠性。这种改进的模型将使研究人员能够更好地利用跨学科的可用数据，并改善对理解地球系统行为至关重要的理论和算法。不幸的是，目前，发现，访问，理解和准备填充这些模型所需的数据所需的时间和精力是大量的时间和精力，以及长时间的学习领先时间，据它们的复杂性，如何使用目前可用的模型。 这项研究通过开发一个可以轻松地集成数据和模型的创新开放建模框架来克服这些局限性，并且易于使用，因此不仅研究社区和运营专业人员可以使用它，还可以使用它，而且还可以使用它。这项渴望的奖励允许建造一个原型开放式元模型框架，该框架在准备工作中的用户的时间和精力大大减少了数据和模型比较，模型测试和验证，以在地表和地下水水文系统中进行基本知识发现。 在此框架中，组件/模块通过用户配置的开放界面进行交互，这些接口可以使用常见的元级体系结构和科学工作流程添加和集成水文模型和数据源。拟议的原型基于最近完成的建模框架HS-NWSRFS（用于改善国家气象服务河预报系统的水力信息系统）。 它代表了来自NASA的三个机构和NWS俄亥俄河预报中心（OHRFC）的调查人员之间的合作。资助的工作将大大将当前代码扩展到开放的社区框架原型。 这项工作的更广泛的影响包括机构间协作，改善对河流的水文预测以及对科学性别不足的PI的支持。