RAPID: Houston in Hurricane Harvey (H3): Establishing Disaster System-of-Systems Requirements for Network-Centric and Data-Enriched Preparedness and Response

这项快速研究将收集和分析休斯敦哈维飓风的时间敏感数据，以便记录在灾难系统(相互依赖的程序、操作和参与备灾和响应的系统)中加强管理、决策和情况感知所需的需求、挑战和所需的能力。灾害系统系统的管理成功和效率取决于整合各个系统和进程以及以网络为中心交流信息的能力。这项研究的成果将包括：(1)研究路线图和本体论，具体说明灾害系统的要求和特征，以便在准备和应对极端天气事件期间提高态势感知、降低风险和决策能力；(2)集成多个不同类型数据集的自动化多模式数据分析框架，以提高对社区风险、事件和活动的态势认识；以及(3)网络分析，为在哪里、向谁以及如何利用智能技术和系统实现以网络为中心和数据丰富的灾害救援系统提供指南。这些成果将为研究人员和实践者提供重要的理解和指导，以创建和实施智能技术和数据分析系统，以增强社区对极端天气事件的复原力。建立强大和有复原力的灾害系统(SOS)对于在极端天气事件中保护社区至关重要。然而，目前的知识缺乏与SOS需求和特征(例如，体系结构、技术和集成)相关的重要元素，无法增强人工流程、交互和决策。为了解决这一知识差距，本研究旨在收集和分析2017年休斯顿哈维飓风的易腐烂和有时间限制的数据，以：(1)通过与民选和任命的官员、基础设施经理、应急人员和决策者以及家庭调查的深入访谈和参与性研讨会，绘制灾害SOS要素、关系、需求和挑战图；(2)研究网络信息学和社会传感技术的效用，以更好地将社交媒体基础设施与灾害SOS相结合，以提高社区对灾难SOS的认识；以及(3)绘制和分析社区网络，根据社区的活动、事件和通信对社区进行建模，以确定利用智能技术进行以网络为中心的准备和响应过程的机会。该项目的结果将产生重大的社会效益，将建立新的智能和互联社区，对极端天气事件具有更强的适应能力。为实现社会效益，将通过三种途径传播项目成果：社区参与讲习班、学术出版物和演示文稿以及项目网页。

This RAPID study will collect and analyze time-sensitive data from Hurricane Harvey in Houston in order to document the needs, challenges, and required capabilities for enhanced management, decision-making, and situation awareness in disaster system-of-systems (interdependent processes, operations, and systems involved in disaster preparedness and response). The management success and efficiency of disaster system-of-systems depend on the ability to integrate individual systems and processes and communicate information in a network-centric manner. The outcomes of this study will include: (1) A research roadmap and ontology specifying the requirements and characteristics for disaster system-of-systems in order to improve situation awareness, risk reduction, and decision-making during preparedness and response to extreme weather events; (2) An automated multi-modal data analytics framework integrating multiple heterogeneous datasets for improved situation awareness of community risks, events, and activities; and (3) A network analysis providing a guide for where, to whom, and how to utilize smart technologies and systems to enable network-centric and data-enriched Disaster SoS. These outcomes will provide important understanding and guide for researchers and practitioners towards creation and implementation of smart technologies and data analytics systems that enhance the resilience of communities to extreme weather events.Establishing robust and resilient disaster system-of-systems (SoS) is essential to protect communities in extreme weather events. However, the current knowledge lacks important elements related to the SoS requirements and characteristics (e.g., architecture, technologies, and integration) to augment human processes, interactions, and decision-making. To address this knowledge gap, this study aims to collect and analyze perishable and time-bound data from the 2017 Hurricane Harvey in Houston to: (1) Map Disaster SoS elements, relationships, needs, and challenges through in-depth interviews and participatory workshops with elected and appointed officials, infrastructure managers, emergency responders, and decision-makers, as well as household surveys; (2) Examine the utility of cyber informatics and social sensing technologies to better integrate social media infrastructure with Disaster SoS for improving the community situation awareness; and (3) Map and analyze community networks to model communities by their activities, events, and communication in order to determine opportunities for utilizing smart technologies for network-centric preparedness and response processes. The outcomes of this project will have significant societal benefits that will build new smart and connected communities that are more resilient to extreme weather events. To attain the societal benefits, the project outcomes will be disseminated through three avenues: community engagement workshops, scholarly publications and presentations, and a project webpage.