CDS&E/Collaborative Research: DataStorm: A Data Enabled System for End-to-End Disaster Planning and Response

CDS

• 批准号: 1610282
• 负责人: Kasim Candan
• 金额: $ 69.28万
• 依托单位: Arizona State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-08-01 至 2022-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1610282&HistoricalAwards=false
• 关键词: CDS&E; Collaborative; Research; DataStorm; Data

Natural disasters affect our society in profound ways. Between 2000 and 2009, disasters killed 1 million people, affected an additional 2.5 million individuals and caused a loss of about $1 trillion (2010 World Disasters Report). Effective disaster response requires a near-real-time effort to match available resources to shifting demands on a number of fronts. Experts today lack the means to provide emergency response agencies with validated strategies for disaster planning and response on a timely basis. Data-driven models and computer simulations for disaster preparedness and response can play a key role in predicting the evolution of disasters and effectively managing emergencies through a diverse set of intervention measures. This project will establish an approach that includes (a) planning disaster response, (b) public information and warning, (c) critical transportation services, (d) mass population care services, and (e) public health and medical services. Effective use of this integrated modeling approach may lead to enhanced safety, quality of life and community resilience. The project also provides an excellent context for doctoral, masters, and undergraduate level research and students will be introduced to career pathways through their participation in research, publication, and partnership with public agencies and data-driven science and engineering researchers.This project will enhance disaster response and community resilience through multi-faceted research to create a big data system to support data-driven simulations with the necessary volume, velocity, and variety and integrate and optimize the key aspects and decisions in disaster management. This includes (a) a novel computational infrastructure capable of executing multiple coupled simulations synergistically, under a unified probabilistic model, (b) addressing computational challenges that arise from the need to acquire, integrate, model, analyze, index, and search, in a scalable manner, large volumes of multi-variate, multi-layer, multi-resolution, and interconnected and inter-dependent spatio-temporal data that arise from disaster simulations and real-world observations, (c) a new high performance data processing system to support continuous observation of the numerical results for simulations from different domains with diverse resource demands and time constraints. These models, algorithms, and systems will be integrated into a disaster data management cyber-infrastructure (DataStorm) that will enable innovative applications and generate broad impacts--through close collaborations with domain experts from transportation, public health, and emergency management--in disaster planning and response.

自然灾害以深远的方式影响我们的社会。在2000年至2009年之间，灾难造成100万人丧生，又影响了250万个人，并损失了约1万亿美元（2010年世界灾难报告）。有效的灾难响应需要近实时的努力，以匹配可用的资源，以改变许多方面的需求。 当今的专家缺乏向应急机构及时提供灾难计划和响应策略的手段。数据驱动的模型和计算机模拟用于灾难准备和响应可以在预测灾难的演变以及通过各种干预措施有效管理紧急情况方面发挥关键作用。 该项目将建立一种方法，其中包括（a）计划灾难响应，（b）公共信息和警告，（c）关键运输服务，（d）大众人口护理服务以及（e）公共卫生和医疗服务。有效使用这种集成建模方法可能会提高安全性，生活质量和社区弹性。该项目还为博士，硕士和本科生的研究提供了一个良好的背景，并将通过参与研究，出版和与公共机构以及数据驱动的科学和工程研究人员的研究，出版和合作伙伴关系来介绍职业途径。该项目将增强灾难响应，并通过多方面的数据系统和多样化的数据系统来增强灾难响应和社区的恢复能力，以使数据和多样化的模拟量身粉量化，并融合了数据，并融合了数据，并逐渐融合了数量，并融合了数量，并融合了数量，并融合了数量，并融合了数量，并将其融合在一起，并将其融合在一起。灾难管理方面的方面和决策。其中包括（a）一个新型的计算基础架构，能够在统一的概率模型下进行多个耦合模拟，协同构造，（b）应对需要获得，集成，模型，分析，索引和搜索的需要，以可扩展的方式，多种多样，多量，多型，多型，且多数，且多数，且多数互换，多数互换，互动，多数互换，且跨度，且多数互换，且跨度互动，多数互换，多数互联，且互联由灾难模拟和现实世界观察引起的时空数据，（c）新的高性能数据处理系统，以支持来自不同资源需求和时间限制的不同领域的模拟的数值结果的连续观察。这些模型，算法和系统将集成到灾难数据管理网络基础结构（Datastorm）中，该网络基础结构将实现创新应用并产生广泛的影响 - 通过与运输，公共卫生和紧急事务管理的领域专家的密切合作 - 在灾难计划和响应中。