ITR/IM+AP: Quality-Scalable Information Flow Systems for Environmental Observation and Forecasting

ITR/IM AP：用于环境观测和预报的质量可扩展的信息流系统

• 批准号: 0121475
• 负责人: Antonio Baptista
• 金额: $ 392.5万
• 依托单位: Oregon Health & Science University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-09-15 至 2007-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0121475&HistoricalAwards=false
• 关键词: ITR; IM+AP; Quality; Scalable; Information

Real-time Environmental Observation and Forecasting Systems (EOFS) will revolutionize the way scientists share information about the environment and represent an opportunity to break traditional information barriers separating scientists from society at large. EOFS are already in use, but they tend to be small-scale, application- and domain- specific, stand-alone systems. There is a need for evolution towards multi-purpose shared systems designed to adapt flexibly to evolving needs of information consumers. What is required are large-scale, shared, heterogeneous distributed systems that make extensive use of diverse sensor-based inputs, sophisticated numerical simulations, mobile and embedded real-time system components, wireless and wired communications, high-performance computers, and high capacity storage systems. This ITR medium project has assembled an inter-disciplinary team, including computer science and environmental science researchers in addition to a heterogeneous base of pilot users. This group will collaborate to develop software technology which will enable EOFS to evolve efficiently, and to deliver quantifiably reliable information about the environment at the right time and in the right form to the right users. The project focus is on EOFS for estuarine and coastal regions. These regions are selected because they are highly variable natural systems subject to intense human activity and with great social, environmental, economic and cultural value.The research will include:i. Developing missing integration concepts and technologies for EOFS, with emphasis on quality-scalable information processing, storage and access (the computer science research).ii. Closing the loop between environmental models and sensors, and implementing a next generation EOFS based on an existing prototype for an estuary with multiple and often conflicting uses (the environmental observation and forecasting systems research);iii. Using, evaluating and refining the EOFS prototype for scientific discovery, natural resources stewardship and emergency response, thus incorporating sound science in operational and management decisions of critical regional importance and national significance (the environmental science and management applications);iv. Developing pilot multi-level, inter-disciplinary educational programs that cross-train young people, computer scientists, environmental scientists and practitioners in the conceptualization, development and use of environmental information technology (the education impact).

实时环境观测和预报系统(EOFS)将彻底改变科学家共享环境信息的方式，并代表着打破将科学家与整个社会分开的传统信息障碍的机会。EOF已经在使用，但它们往往是小规模的、特定于应用程序和域的独立系统。需要朝着旨在灵活适应信息消费者不断变化的需求的多用途共享系统发展。所需要的是大规模的、共享的、异质的分布式系统，这些系统广泛使用各种基于传感器的输入、复杂的数值模拟、移动和嵌入式实时系统组件、无线和有线通信、高性能计算机和大容量存储系统。这个ITR Medium项目组建了一个跨学科团队，除了试点用户之外，还包括计算机科学和环境科学研究人员。该小组将合作开发软件技术，使EOFs能够高效地发展，并在正确的时间以正确的形式向正确的用户提供有关环境的可量化的可靠信息。该项目的重点是河口和沿海地区的EOFs。选择这些区域是因为它们是受强烈人类活动影响的高度可变的自然系统，具有巨大的社会、环境、经济和文化价值。研究将包括：i.为EOFs开发缺失的集成概念和技术，重点是质量可扩展的信息处理、存储和访问(计算机科学研究)。关闭环境模型和传感器之间的环路，并在具有多种用途且往往相互冲突的河口的现有原型的基础上实施下一代EOFS(环境观测和预报系统研究)；使用、评估和完善用于科学发现、自然资源管理和应急反应的环境科学框架原型，从而将健全的科学纳入具有重大区域意义和国家意义的业务和管理决策(环境科学和管理应用)；制定多层次、跨学科的试点教育方案，对年轻人、计算机科学家、环境科学家和从业人员进行环境信息技术概念化、开发和使用方面的交叉培训(教育影响)。