Abstract: Identifying a chemical, biological, radiological, and nuclear incident (CBRN) is a challenge. Evidence and health symptoms resulting from CBRN malevolent incident overlap with other normal non malevolent human activities. However, proper fusion of symptoms and evidence can aid in drawing conclusions with a certain degree of credibility about the existence of an incident. There are two types of incidents directly observable, overt, or indirectly observable, covert, which can be detected from the symptoms and consequences. This paper describes a framework for identifying a CBRN incident from available evidence using a fuzzy belief degree distributed approach. We present two approaches for evidence fusion and aggregation; the first, two level cumulative belief degree (CBD) while the second is ordered weighted aggregation of belief degrees (OWA). The evaluation approach undertaken shows the potential value of the two techniques.

Abstract: In this document, we describe the need for providing a uniform common picture that is missing in several crisis management decision support tools. Through research, we have reviewed some existing crisis management support systems in use and noted key user requirements that these tools are missing. A significant point of this research is to stress the importance of developing a decision support system that would improve the way an ideal support system would collect, analyze and disseminate necessary information to a crisis management decision maker. We also note the importance of ensuring that such a tool presents information to its user over a user friendly interface. The structure thus developed should be a standalone application that could be incorporated into existing platforms (Rinkineva, 2004) such as cell phones, PDAs and laptops.

Abstract: Project ERMA (Electronic Risk Management Architecture) develops a platform for risk managers that can be cus-tomised to individual risk management scenarios in order to meet the needs of small and medium-sized municipali-ties. Due to their limited resources, smaller boroughs call for flexible and intelligent platforms that can be tailored to a set of risk management scenarios that might range from natural disasters to man-made hazards. This paper will promote a process-oriented stance for supporting emergency management operations. The scope of services ranges from decision support via key-indicators with attached process management system up-to alarming services that incorporate citizen relationship management services to keep the citizen well informed and use him for the capture of additional information.

Abstract: Decision making in case of any emergency is associated with uncertainty of input data, model data and changing preferences in the decision making process. Uncertainty handling was from the beginning an integral part of the decision support system RODOS for the off-site emergency management following nuclear or radiological emergencies. What is missing so far is the visualisation of the uncertainties in the results of the model calculations. In this paper we present the first attempt to visualise uncertain information in the early and late phase of the decision making process. For the early phase, the area of sheltering was selected as example. For the later phase, the results of the evaluation subsystem of RODOS were selected being used for the analysis of remediation measures such as agricultural management options. Both attempts are still under discussion but the presentation of the early phase uncertainty will be realised in the next version.

Abstract: Today's decision support systems for crisis management are mostly designed to support a fixed process that integrates a given set of information sources. This means policies that govern the crisis management process are tightly integrated with the implementation, which makes it hard to adapt the system to changing requirements. Modern systems are expected to be adaptable and need to evolve along with the availability of new information sources and changing business processes. Previous work suggested using workflow systems to manage crisis management processes. Current approaches that use workflow systems are not end-user friendly or not flexible enough. In this paper we present our approach that combines workflows and decision tables for creating more flexible decision support systems. While workflows are used to orchestrate services and implement information logistics in the decision support processes, embedded rule sets are used to provide flexibility and adaptability of workflows. The rule sets are authored using decision tables which are an easy-to-use representation that allows end-users to express rules in an intuitive way. © 2012 ISCRAM.

Abstract: The generation and supply of electricity is currently about to undergo a fundamental transition that includes extensive development of smart grids. Smart grids are huge and complex networks consisting of a vast number of devices and entities which are connected with each other. This fact opens new variations of disruption scenarios which can increase the vulnerability of a power distribution network. However, the network topology of a smart grid has significant effects on urban resilience particularly referring to the adequate provision of vital services of critical infrastructures. An elaborated topology of smart grids can increase urban resilience. In this paper, we discuss the role of smart grids, give research impulses for examining diverse smart grid topologies and for evaluating their impacts on urban resilience by using an agent based simulation approach which considers smart grid topology as a model parameter.

Abstract: Building up proper situation awareness is one of the most difficult tasks in the beginning stages of large-scale accidents. As ambiguous information about the events becomes available, decision makers are often tempted to quickly choose a particular story to explain the events. Subsequent information that contradicts the initial story may easily be discarded and cognitive tunnel vision takes over. Our approach, as part of the COMBINED Systems project, is to prevent tunnel vision by providing critical thinking support. In a laboratory experiment with 60 participants, we tested this hypothesis by comparing the Critical Thinking tool with a 'no support' control condition and a 'minimal support' condition. Participants acted as crisis managers determining the likely cause of an accident based on different pieces of information. The results show a positive impact of the tool on both the decision making process and decision making effectiveness.

Abstract: In recent years, various crises arise frequently and cause tremendous economic and life losses. Meanwhile, current emergency decision models and decision support systems still need further improvement. This paper first proposes a new emergency decision model based on the combination of a new case retrieval algorithm for Case-Based Reasoning (CBR) and logic reasoning, and then address a sample flood disaster emergency decision process to explain the application of the model in practice.

Abstract: The evaluation of an emergency scenario is often based on the use of simulation models. The specificity of these models involves the need for a complex evaluation of the problem domain, including the physical conditions behind the considered threat. Based on emergency occurrences data, provided by the Portuguese National Civil Protection Authority, we are currently developing a methodology for evaluating a real situation, based on past occurrences. The aim is to develop a platform that will enable the evaluation of a risk scenario based on existing civil protection data. The methodology under development should enable the evaluation of different scenarios based on the collected available data. This will be achieved thanks to the facilitated configuration of several aspects, such as the geographical region and relevant properties of the considered threat. In this paper, we describe the methodology development process and the current state of the platform for risk evaluation.

Abstract: The paper addresses the issue of context-aware operational decision support in emergency situations. A decision support system (DSS) developed for this purpose is implemented as a network of a set of Web-services. The Web-services try to organise a service network according to context. Here the context is proposed to be modelled as a “problem model”. It specifies problems to be solved in a particular kind of emergency situation. Context is produced based on the knowledge extracted from the application domain (application ontology) and formalised by a set of constraints. The purpose of the service network is provision the DSS with contextualised information from diverse information sources and solving problems specified in the context. In the framework of context-aware operational decision support, composition of the application ontology for the disaster management domain from the Semantic Web Ontologies is discussed and a hybrid technology of context-aware operational decision support is presented. The technology is based on ontology management, context management, constraint satisfaction, and Web Services. Application of the ideas above is illustrated by an example of a decision support system for real-time resource coordination and situation awareness for logistics management in fire response operations.

Abstract: Emergency management is by its nature, and in some jurisdictions by its definition, an activity that requires a concerted effort by a number of governmental and non-governmental agencies. There is a growing appreciation that collaboration between these parties is best served through the use of interoperable standards for message formats for purposes such as alerting and resource exchange. However, it is also important to realize that, although much advantage can be drawn from standardizing certain aspects of communication, such as the structure of messages, different agencies will use different vocabularies. In this paper we discuss how ontologies can be used with standard messaging formats for resource messaging to enable intelligent decision support mechanisms in the presence of differing vocabularies across organizational boundaries. We also present a survey of the opportunities for using ontologies in emergency management, and the issues that must be addressed.

Abstract: The purpose of this field study was investigate teamwork and communication among event management personnel, to assess the degree to which PROBE, the advanced prototype they were using to manage a CBRNE simulation, would adequately meet their needs. The study was a continuation of previous research conducted in the early phase of PROBE development. Two communication-related analyses were applied to identify instances of effective and of ineffective communication among the management team. These revealed that communication was mostly effective. However, the one serious communication breakdown that was observed could have had fatal consequences. It showed that great care must be taken to ensure the safety of first responders at all times when evaluating prototypes in the field. A list of questions was generated from the lessons learned to assist future researchers prepare for CBRNE field studies.

Abstract: This research presents the conceptual Business Intelligence (BI) model for disaster management. BI can provide agility capacity for decision making in dynamic environment among different agencies. This project designs and develop a data warehouse using multi-dimensional model for severity analysis of flood and landslide in risk area using case study from Department of disaster prevention and mitigation (DDMP), Phuket, Thailand. The concept of BI can be applied for extremely heterogeneous data structures and data platform environment to improve data quality and expose to better decision-making for disaster management. In the next stage of this project, we will integrate more data sources from other agencies for example GIS data from Phuket land-use planning and flooding prediction model database. The result of this study will help organization deploy BI more effectively.