Abstract: This paper presents observations made in the course of two interorganizational crisis management exercises that were conducted in order to identify requirements for a decision support system for critical infrastructure operators. It brings into focus how different actors deal with the uncertainty of information that is relevant for other stakeholders and therefore is to be shared with them. It was analyzed how the participants articulated und comprehended assessments on how probable the reliability of a given data or prognosis was. The recipients of the information had to consider it when making decisions concerning their own network. Therefore they had to evaluate its reliability. Different strategies emerged.

Abstract: We are interested in rescue management in crises such as in terrorist attacks. Today, there are emergency plans that take into account all the stakeholders involved in a crisis depending on the event type, magnitude and place. Unfortunately, they do not anticipate the evolution of the crisis situation such as traffic and hospital overcrowding. In addition, decisions are taken after the information has been passed from the operational level to higher levels. This work focuses on the operational level of the emergency plan. What will happen if the actors at this level, can make certain decisions without escalating the information to higher levels? To answer this question, a multi-agent dynamic planning approach is proposed and it will be tested in two different architectures in order to see how much autonomy can be given to an agent and how they coordinate to save the victims.

Abstract: Social Media monitoring has become a major issue in crisis and emergencies management. Indeed, social media may ease the sharing of information between citizens and Public Safety Organizations, but it also enables the rapid spreading of inaccurate information. As information is now provided and shared by anyone to anyone, information credibility is a major issue. We propose an approach to detect rumor in social media. This paper describes our work on semantic graph based information fusion, enhanced with uncertainty management capabilities. The uncertainty management capability enables managing the dierent level of credibility of actors of an emergency (dierent PSO oÿcers and citizens). Functions for information synthesis, conflicting information detection and information evaluation were developed and test during experimentation campaigns. The synthesis and conflicting information detection functionalities are very welcome by end-users. However, the uncertainty management is a combinatorial approach which remains a limitation for use with large amount of information.

Abstract: Often, water management decisions are based on hydrological forecasts, which are affected by inherent uncertainties. It is increasingly common for forecasters to make explicit estimates of these uncertainties. Associated benefits include the decision makers' increased awareness of forecasting uncertainties and the potential for risk-based decision-making. Also, a more strict separation of responsibilities between forecasters and decision maker can be made. A recent study identified some issues related to the effective use of probability forecasts. These add a dimension to an already multi-dimensional problem, making it increasingly difficult for decision makers to extract relevant information from a forecast. Secondly, while probability forecasts provide a necessary ingredient for risk-based decision making, other ingredients may not be fully known, including estimates of flood damage and costs and effect of damage reducing measures. Here, we present suggestions for resolving these issues and the integration of those solutions in a prototype decision support system (DSS). A pathway for further development is outlined.

Abstract: During the past quarter century there have been many developments in scientific models and computer codes to help predict the ongoing consequences in the aftermath of many types of emergency: e.g. storms and flooding, chemical and nuclear accident, epidemics such as SARS and terrorist attack. Some of these models relate to the immediate events and can help in managing the emergency; others predict longer term impacts and thus can help shape the strategy for the return to normality. But there are many pitfalls in the way of using these models effectively. Firstly, non-scientists and, sadly, many scientists believe in the models' predictions too much. The inherent uncertainties in the models are underestimated; sometimes almost unacknowledged. This means that initial strategies may need to be revised in ways that unsettle the public, losing their trust in the emergency management process. Secondly, the output from these models form an extremely valuable input to the decision making process; but only one such input. Most emergencies are events that have huge social and economic impacts alongside the health and environmental consequences. While we can model the latter passably well, we are not so good at modelling economic impacts and very poor at modelling social impacts. Too often our political masters promise the best 'science-based' decision making and too late realise that the social and economic impacts need addressing. In this paper, we explore how model predictions should be drawn into emergency management processes in more balanced ways than often has occurred in the past. © Proceedings ISCRAM 2004.

Abstract: Survey researchers need to, Find out what assumptions evacuation modelers are making and collect empirical data to replace incorrect assumptions;, Obtain data on the costs of evacuation to households, businesses, and local government; and, Extend their analyses to address the logistics of evacuation and the process of re-entry. Evacuation modelers need to, Incorporate available empirical data on household evacuation behavior, and, Generate estimates of the uncertainties in their analyses. Cognitive scientists need to, Conduct experiments on hurricane tracking and evacuation decision making to better understand these processes, and, Develop training programs, information displays, and performance aids to assist local officials who have little or no previous experience in hurricane evacuation decision making.

Abstract: Protecting critical infrastructures (CIs) against external and internal risks in an increasingly uncertain environment is a major challenge. In this paper we present a generic multi-stage scenario construction approach that is applicable to a wide range of decision problems in the field of CI protection. Our approach combines scenario construction and decision support, whereby we explicitly consider the performance of decision options which have been determined for a set of initial scenarios. Because of the iterative character of our approach, consequences of decision options and information updates are evolutionary processed towards advanced scenarios. By disturbing vulnerable or critical parts of CIs, cascading effects between interrelated CIs and the responses to the decision options can be determined. We apply this scenario-construction technique to two civil security research projects. One focuses on protecting food supply chains against disruptions, whereas the other aims at securing public railway transport against terrorist attacks.

Abstract: Emergencies are characterised by uncertainty. This motivates the design of information systems that model and predict complex natural, material or human processes to support understanding and reduce uncertainty through prediction. The correspondence between system models and reality, however, is also governed by uncertainties, and designers have developed methods to render ?the world? transparent in ways that can inform, fine-tune and validate models. Additionally, people experience uncertainties in their use of simulation and prediction systems. This is a major obstacle to effective utilisation. We discuss ethically and socially motivated demands for transparency.

Abstract: In the Netherlands, Royal Dutch Meteorological Institute warns water boards for extreme rainfall if per-specified thresholds are (expected to be) exceeded. When a water board receives a warning, certain response measures can be taken. In general, the thresholds are based on experience and intuition. Clear procedures, which describe decision-making under uncertainty in available information (e.g., forecasted rainfall), do not exist. In this document, first results of the project “Extreme weather for water boards” are briefly described. The aim of this project is to study integration of the uncertainty into emergency procedures of the water boards. The current emergency procedures of two water boards are analyzed. Recommended adjustments to the procedures allow including the uncertainty by estimation of a probability of overload and cost-benefit analysis of response measures (benefit as avoided damage). A simple scheme that supports estimation of the probability is introduced. © 2012 ISCRAM.