CEO:P--A Data-Intensive Cyberinfrastructure Component for Coastal Forecasting and Change Analysis

摘要OCI 0619041多年来，人们在观测和模拟环境方面做了大量的工作。许多复杂的系统已经或正在建立。尽管正在收集的数据量的进步，（包括更大数量的源以及增加的时空粒度）和用于分析这些数据集的技术的增强，在这一领域仍然存在许多挑战。首先，当前的系统是紧密耦合的。在不同的系统中几乎没有算法实现的重用。测试或采用新的分析算法也非常困难。这些实现与可用资源密切相关，最后，现有的系统不能使分析的粒度适应资源可用性和时间约束。面向服务的体系结构和网格计算（密切相关）概念的出现趋势可以缓解上述问题。它们可以支持不绑定到特定数据集或终端应用程序的服务的开发，以及使用这些服务的应用程序的实现。然而，这也需要在网格中间件组件，能够支持流媒体应用程序和数据虚拟化/integration.This项目提出了开发和评估网络基础设施组件的环境应用程序的进步。这将包括开发中间件、模型集成、分析和挖掘技术，以及使用服务模型来支持两个密切相关的应用程序。这些应用将是实时海岸现在铸造和预报，以及长期的海岸侵蚀分析和预测。所处理的具体问题如下。在第一个应用程序中，重点将放在实时现在铸造和沿海条件的预测。 将使用中间件和面向服务的执行工作，以便能够插入新的算法（例如，海滩关闭和大肠菌群预测），能够根据资源和时间限制使用更复杂的模型，能够灵活地插入新的数据流，并能够对预测/现播模型产生的数据采用新的分析和解释算法。在第二个应用程序中，将开发用于长期海岸变化和侵蚀模式的高级模型，并允许进行更大规模，分布式和灵活的数据分析。将在五大湖观测系统的范围内与国家海洋和大气层管理局（诺阿）联合执行和评价。 这是一个很好的机会，进行现实的设计，部署和评估的网络基础设施的组成部分，也影响长期的设计和操作的一个真实的环境观测系统。这个项目将是一个共同努力之间的俄亥俄州州立大学（OSU）和国家海洋和大气管理局（NOAA）。俄勒冈州立大学的团队包括两名计算机科学研究人员：Gagan Agrawal（网格中间件系统）和Hakan Ferhatosmanoglu（数据库和数据分析），以及两名环境研究人员：基思贝德福德（环境建模）和罗恩李（地理空间数据分析和遥感）。NOAA的合作者包括NOAA-国家海洋服务（NOS）的Frank Aikman博士和NOAA -五大湖环境研究实验室（GLERL）的大卫施瓦布博士。

Abstract OCI 0619041Over the years, much work has been done on observing and modeling the environment. Many complex systems have been, or are being, built. Despite advances in the amount of data being collected, (including larger number of sources as well as increased spatio-temporal granularity) and enhancements in the techniques being used for analyzing these datasets, a number of challenges remain in this area. Firstly, the current systems are very tightly coupled. There is hardly any reuse of algorithm implementations across different systems. It is also extremely hard to test or incorporate new analysis algorithms. The implementations are closely tied to the available resources, and finally, the existing systems cannot adapt the granularity of analysis to the resource availability and time constraints. The emerging trend towards (closely related) concepts of service-oriented architectures and grid computing can alleviate the above problems. They can enable development of services that are not tied to specific datasets or end applications, and implementation of applications using these services. However, this also requires advances in grid middleware components that are able to support streaming applications and data virtualization/integration.This project proposes to develop and evaluate a cyberinfrastructure component for environmental applications. This will include developments in middleware, model integration, analysis, and mining techniques, and the use of a service model for supporting two closely related applications. These applications will be real-time coastal now casting and forecasting, and long term coastal erosion analysis and prediction. The specific problems addressed are as follows. In the first application, focus will be on real-time now casting and forecasting of coastal conditions. Middleware and service-oriented implementation will be used to allow new algorithms to be inserted (for example, for beach closings and coliform forecasts), allow more complex models to be used based on resource and time constraints, allow new data streams to be inserted flexibly, and allow new algorithms for analysis and interpretation to be operated on data being produced from forecasting/now casting models. In the second application, advanced models will be developed for long-term coastal changes and erosion patterns, and allow larger scale, distributed, and flexible data analysis. Implementation and evaluation will be in the context of the Great Lakes Observing System (GLOS) and will be done jointly with the National Oceanic and Atmospheric Administration (NOAA). This is an excellent opportunity to carry out realisticdesign, deployment, and evaluation of the cyberinfrastructure component, and also impact the long-term design and operation of a real environmental observation system.This project will be a joint effort between The Ohio State University (OSU) and the National Oceanic and Atmospheric Administration (NOAA). The OSU team includes two computer science researchers: Gagan Agrawal (grid middleware systems) and Hakan Ferhatosmanoglu (databases and data analysis), and two environmental researchers: Keith Bedford (environmental modeling) and Ron Li (geospatial data analysis and remote sensing). The NOAA collaborators include Dr. Frank Aikman,NOAA-National Ocean Service (NOS), and Dr. David Schwab, NOAA -Great Lakes Environmental Research Lab (GLERL).