Ummul Khair Israt Ara, & Fang Chen. (2012). Information security in crisis management system. In Z.Franco J. R. L. Rothkrantz (Ed.), ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management. Vancouver, BC: Simon Fraser University.
Abstract: Information security is an important part of almost any kind of Information System. Crisis Management Systems (CMS) are a type of Information System that deals with information which needs to be secure. No matter what kind of crisis, natural disasters, man-made crisis or terrorist attacks, the CMS security should not be compromised. There are many challenges regarding exchange of qualified information and interoperability between various Expert Systems and the CMS. It is important to have strong security in terms of technology, skills, security requirements, sensitivity of information and trust-worthiness (Vural, Ciftcibasi and Inan, 2010). Depending on the type of crisis situation, different sets of security components should be triggered, since the security requirements vary between situations. For example, a terrorist attack has different security requirements in the system compared to a natural disaster or a medical emergency. In this paper, the importance of Information Security in CMS will be discussed. Methods for secure exchange of qualified information are analyzed and a secure and dynamic Crisis Management Information Security System (CMISS) design is introduced. © 2012 ISCRAM.
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Seyed Hossein Chavoshi, Mahmoud Reza Delavar, Mahdieh Soleimani, & Motahareh Chavoshi. (2008). Toward developing an expert GIS for damage evaluation after an earthquake (case study: Tehran). In B. V. de W. F. Fiedrich (Ed.), Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management (pp. 734–741). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: In an earthquake disaster, having proper estimation about destructed buildings and the degree of destruction, can considerably facilitate decision-making and planning for disaster managers. Using this information, the managers can estimate disaster area and number of victims to determine and allocate required resources. Scientific studies and historical data show that the faults around Tehran, the capital of Iran, are capable to create strong earthquakes which would bring the largest damages in the world history to the city. So it is necessary to be prepared for a rapid and knowledge-based response to such an earthquake. Therefore, development of a knowledge-based model to estimate destruction of buildings is ongoing. The model is going to be developed by using different spatial data obtained from the buildings and its environment in Tehran. This paper outlines the initial results of this research.
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Tina Comes, Claudine Conrado, Michael Hiete, Michiel Kamermans, Gregor Pavlin, & Niek Wijngaards. (2010). An intelligent decision support system for decision making under uncertainty in distributed reasoning frameworks. In C. Zobel B. T. S. French (Ed.), ISCRAM 2010 – 7th International Conference on Information Systems for Crisis Response and Management: Defining Crisis Management 3.0, Proceedings. Seattle, WA: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: This paper presents an intelligent system facilitating better-informed decision making under severe uncertainty as found in emergency management. The construction of decision-relevant scenarios, being coherent and plausible descriptions of a situation and its future development, is used as a rationale for collecting, organizing, filtering and processing information for decision making. The development of scenarios is geared to assessing decision alternatives, thus avoiding time-consuming analysis and processing of irrelevant information. The scenarios are constructed in a distributed setting allowing for a flexible adaptation of reasoning (principles and processes) to the problem at hand and the information available. This approach ensures that each decision can be founded on a coherent set of scenarios, which was constructed using the best expertise available within a limited timeframe. Our theoretical framework is demonstrated in a distributed decision support system by orchestrating both automated systems and human experts into workflows tailored to each specific problem.
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Ola Leifler, & Johan Jenvald. (2005). Critique and visualization as decision support for mass-casualty emergency management. In B. C. B. Van de Walle (Ed.), Proceedings of ISCRAM 2005 – 2nd International Conference on Information Systems for Crisis Response and Management (pp. 155–159). Brussels: Royal Flemish Academy of Belgium.
Abstract: Emergency management in highly dynamic situations consists of exploring options to solve a planning problem. This task can be supported through the use of visual cues that are based on domain knowledge of the current domain. We present an approach to use visualization of critical constraints in timelines and hierarchical views as decision support in mass-casualty emergency situations.
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Julio Camarero Puras, & Carlos A. Iglesias. (2009). Disasters2.0. Application of Web2.0 technologies in emergency situations. In S. J. J. Landgren (Ed.), ISCRAM 2009 – 6th International Conference on Information Systems for Crisis Response and Management: Boundary Spanning Initiatives and New Perspectives. Gothenburg: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: This article presents a social approach for disaster management, based on a social portal, so-called Disasters2.0, which provides facilities for integrating and sharing user generated information about disasters. The architecture of Disasters2.0 is designed following REST principles and integrates external mashups, such as Google Maps. This architecture has been consumed with different clients, including a mobile client, a multiagent system for assisting in the decentralized management of disasters, and an expert system for automatic assignment of resources to disasters. As a result, the platform allows seamless collaboration of humans and intelligent agents, and provides a novel web2.0 approach for multiagent and disaster management research.
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