Information Technology Research (ITR): Responding to the Unexpected

该项目的长期目标是从根本上改变应对人为和自然灾害的组织在应急机构内部和向公众收集、处理、管理、使用和传播信息的能力。该项目探讨了一个多学科的方法，包括两个相互关联的研究重点：-可扩展的和强大的信息技术解决方案，以促进获得正确的信息，由正确的个人和组织，在正确的时间，和-社会科学研究，调查动态虚拟组织的独特性质，以及跨组织和个人的信息共享的社会和文化方面。研究的挑战包括机制：使危机应对者成为重要的情况信息的丰富来源;无缝地收集来自不同来源的数据;将低层次的嘈杂数据转化为有意义的信息，可以有效地用于损害评估和情况意识;促进信息共享和集体决策的新兴虚拟组织;并以对接收者最有用的形式迅速传播信息。与多个政府机构的密切合作已经发展到在现场环境中测试和验证研究。预计该项目将产生强大的信息系统，使第一反应者能够作出知情和更好的决定，确定其反应的优先次序，并侧重于最有可能拯救生命和财产的活动。由此产生的及时和有效的反应可以遏制或预防次生灾害，并减少灾害期间造成的经济损失和社会混乱。该项目将为文本、视频和数据挖掘创建新的共享数据集。这将允许更大的科学界根据这些现场收集的数据集测试算法创新。我们的社区外展计划将有助于提高人们对IT作用的认识，刺激新的创新，因为急救人员与研究人员的互动更加密切。我们的教育计划将产生一支训练有素的危机管理工作队伍。

The long-term goals of this project are to radically transform the ability of organizations that respond to man-made and natural disasters to gather, process, manage, use and disseminate information both within the emergency response agencies and to the general public. The project explores a multidisciplinary approach consisting of two interrelated research thrusts:- Scalable and robust information technology solutions to facilitate access to the right information, by the right individuals and organizations, at the right time, and- Social science research that investigates the distinctive nature of dynamic virtual organizations, and the social and cultural aspects of information sharing across organizations and individuals. Research challenges addressed include mechanisms to: enable crisis responders to become rich sources of vital situational information; seamlessly collect data from heterogeneous sources; translate low-level noisy data into meaningful information that can be effectively used for damage assessment and situation awareness; facilitate information sharing and collective decision-making across emergent virtual organizations; and rapidly disseminate information in the form most useful to recipients. Close collaborations with multiple government agencies have been developed to test and validate research in live environments. The project is expected to result in robust information systems that enable first responders to make well-informed and better decisions, to prioritize their response, and to focus on activities that have the highest potential to save lives and property. The resulting timely and effective response can contain or prevent secondary disasters, and reduce the resulting economic losses and social disruption during disasters. The project will create new shared data sets for text, video and data mining. This will allow a larger scientific community to test algorithmic innovations against these field gathered data sets. Our community outreach programs will help generate greater awareness of the role of IT, stimulating new innovations as first responders interact more closely with researchers. Our educational programs will generate a better trained crisis management work force.