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Abbas Ganji, Negin Alimohammadi, & Scott Miles. (2019). Challenges in Community Resilience Planning and Opportunities with Simulation Modeling. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: The importance of community resilience has become increasingly recognized in emergency management and
post-disaster community well-being. To this end, three seismic resilience planning initiatives have been
conducted in the U.S. in the last decade to envision the current state of community resilience. Experts who
participated in these initiatives confronted challenges that must be addressed for future planning initiatives.
We interviewed eighteen participants to learn about the community resilience planning process, its
characteristics, and challenges. Conducting qualitative content analysis, we identify six main challenges to
community resilience planning: complex network systems; interdependencies among built environment systems;
inter-organizational collaboration; connections between the built environment and social systems;
communications between built environment and social institutions? experts; and communication among
decision-makers, social stakeholders, and community members. To overcome the identified challenges, we
discuss the capability of human-centered simulation modeling as a combination of simulation modeling and
human-centered design to facilitate community resilience planning.
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Adam Widera, Hanns-Alexander Dietrich, Bernd Hellingrath, & Jörg Becker. (2013). Understanding humanitarian supply chains – Developing an integrated process analysis toolkit. In J. Geldermann and T. Müller S. Fortier F. F. T. Comes (Ed.), ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management (pp. 210–219). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: In this paper we present the development of an integrated process analysis toolkit for humanitarian logistics. The toolkit integrates a conceptual and a technological component. Our approach follows a case study-based modeling and design approach. The developed concept was evaluated in two humanitarian organizations. Based on these results we extended and integrated the tool-supported process analysis approach, which is ready to use for the structural and quantitative analysis of humanitarian logistics processes. The toolkit can be applied in humanitarian organizations as a decision support tool for designing, planning and executing their logistics processes. Thus, the application affects the preparedness of humanitarian organizations as well as their response performance. The process analysis toolkit is embedded in an overall research agenda with the objective to provide humanitarian organizations with the capabilities to identify, monitor, and improve their logistics processes respecting the organization specific objectives.
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Ahmed Abdeltawab Abdelgawad. (2019). Reliability of expert estimates of cascading failures in Critical Infrastructure. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: Owing to the complexity of Critical Infrastructures and the richness of issues to analyze, numerous approaches are used to model the behavior of CIs. Organizations having homeland security as mission often conduct desktop-based simulations using judgmental assessment of CI interdependencies and cascading failures. Expert estimates concern direct effects between the originally disrupted CI sector and other sectors. To better understand the magnitude of aggregate cascading effects, we developed a system dynamics model that uses expert estimates of cascading failures to compare the aggregate effect of cascading failures with the primary direct cascading failures. We find that the aggregate effect of compounded cascading failures becomes significantly greater than the primary cascading failures the longer the duration of the original disruption becomes. Our conceptually simple system dynamics model could be used to improve desktop-based exercises, since it illustrates consequences that go beyond judgmental assessment.
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Ahmed Laatabi, Benoit Gaudou, Chihab Hanachi, Patricia Stolf, & Sébastien Truptil. (2022). Coupling Agent-based Simulation with Optimization to Enhance Population Sheltering. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 116–132). Tarbes, France.
Abstract: Population sheltering is a recurrent problem in crisis management that requires addressing two aspects: evacuating vulnerable people using emergency vehicles and regulating movements of pedestrians and individual vehicles towards shelters. While these aspects have received considerable attention in modeling and simulation literature, very few approaches consider them simultaneously. In this paper, we argue that Agent-Based Modeling and Simulation (ABMS) and Optimization are two complementary approaches that can address the problem of sheltering globally and efficiently and be the basis of coherent frameworks for decision- and policy-making. Optimization can build efficient sheltering plans, and ABMS can explore what-if scenarios and use geospatial data to display results within a realistic environment. To illustrate the benefits of a framework based on this coupling approach, we simulate actual flash flood scenarios using real-world data from the city of Trèbes in South France. Local authorities may use the developed tools to plan and decide on sheltering strategies, notably, when and how to evacuate depending on available time and resources.
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Alayne Da Costa Duarte, Marcos R. S. Borges, Jose Orlando Gomes, & De Paulo V. R. Carvalho. (2013). ASC model: A process model for the evaluation of simulated field exercises in the emergency domain. In J. Geldermann and T. Müller S. Fortier F. F. T. Comes (Ed.), ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management (pp. 551–555). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: The undefined flow of execution of activities in an evaluation process hampers its implementation. A consistent evaluation process defines interrelated methodological steps that make it easier for the evaluator to lead the process. This article presents a process model for the evaluation of simulated field exercises in the emergency domain, including their sub processes and activities. The proposed model was derived from observations made during real situations of a simulated evacuation exercise of communities in high-risk areas in Rio de Janeiro (Brazil). The motivation came from the finding that the assessment of simulated field exercises is conducted by completing an activity report that does not follow a structural model, an evaluation program or a formal standard. The results of this research show the experts' satisfaction with the application of the model proposed for the development of an evaluation process. The same occurs when comparing to reports currently used by them for this purpose.
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Alexander Gabriel, Babette Tecklenburg, Yann Guillouet, & Frank Sill Torres. (2021). Threat analysis of offshore wind farms by Bayesian networks – a new modeling approach. In Anouck Adrot, Rob Grace, Kathleen Moore, & Christopher W. Zobel (Eds.), ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management (pp. 174–185). Blacksburg, VA (USA): Virginia Tech.
Abstract: As a result of the ongoing commitment to climate protection in more and more countries and the corresponding expansion of renewable energies, the importance of renewables for the security of electricity supply is also increasing. Wind energy generated in offshore wind farms already accounts for a significant share of the energy mix and will continue to grow in the future. Therefore, approaches and models for security assessment and protection against threats are also needed for these infrastructures. Due to the special characteristics and geographical location of offshore wind farms, they are confronted with particular challenges. In this context, this contribution outlines how an approach for threat analysis of offshore wind farms is to be developed within the framework of the new research project “ARROWS” of the German Aerospace Center. The authors first explain the structure of offshore wind farms and then present a possible modeling approach using Qualitative function models and Bayesian networks.
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Alexander Smirnov, Tatiana Levashova, Andrew Krizhanovsky, Nikolay Shilov, & Alexey Kashevnik. (2009). Self-organizing resource network for traffic accident response. 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: Traffic accidents are a common feature of the modern life. The paper proposes an approach addressing response to traffic accidents happened in a smart environment. The idea behind the approach is to self-organize resources of the environment according to the state of the situation caused by the accident. The resources self-organize a collaborative network that comprises physical devices, software services, organizations, and persons. The purpose of the resources is to undertake joint actions for accident response. The disaster response system intended for operating in smart environments has a service-oriented architecture. Some of Web-services making up the architecture are intended to model the accident situations; others model resource functionalities or bear supporting functions. Web-services that model resource functionalities are aligned against the disaster management ontology. This alignment ensures semantic interoperability of the heterogeneous resources. The alignment operation is supported by a tool that identifies similar concepts in the ontology and Web-service descriptions using a machine-readable dictionary. Response to the traffic accident illustrates main ideas described in the paper.
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Ben Ortiz, Laura Kahn, Marc Bosch, Philip Bogden, Viveca Pavon-Harr, Onur Savas, et al. (2020). Improving Community Resiliency and Emergency Response With Artificial Intelligence. In Amanda Hughes, Fiona McNeill, & Christopher W. Zobel (Eds.), ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management (pp. 35–41). Blacksburg, VA (USA): Virginia Tech.
Abstract: New crisis response and management approaches that incorporate the latest information technologies are essential in all phases of emergency preparedness and response, including the planning, response, recovery, and assessment phases. Accurate and timely information is as crucial as is rapid and coherent coordination among the responding organizations. We are working towards a multi-pronged emergency response tool that provide stakeholders timely access to comprehensive, relevant, and reliable information. The faster emergency personnel are able to analyze, disseminate and act on key information, the more effective and timelier their response will be and the greater the benefit to affected populations. Our tool consists of encoding multiple layers of open source geospatial data including flood risk location, road network strength, inundation maps that proxy inland flooding and computer vision semantic segmentation for estimating flooded areas and damaged infrastructure. These data layers are combined and used as input data for machine learning algorithms such as finding the best evacuation routes before, during and after an emergency or providing a list of available lodging for first responders in an impacted area for first. Even though our system could be used in a number of use cases where people are forced from one location to another, we demonstrate the feasibility of our system for the use case of Hurricane Florence in Lumberton, a town of 21,000 inhabitants that is 79 miles northwest of Wilmington, North Carolina.
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Christian Sell, & Iris Braun. (2009). Using a workflow management system to manage emergency plans. 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: In the event of a disaster in Germany a so-called executive staff is set up. In support of their work they refer to emergency plans, which describe the chronological order of a set of suitable measures for a dedicated event e.g. an evacuation. These plans only exist in the form of large printed documents. Hence, the technical support for executing emergency plans is very limited. In this paper we present a model for a workflow management system (WfMS) for supporting the modeling, execution and management of emergency plans before and during a disaster. It is based on the idea that emergency plans are similar to business processes and can therefore be modeled as workflows. In contrast to most traditional WfMS, the introduced approach supports unstructured activities and their delegation as well as the management of resources. Furthermore, we analyze drawbacks of the current process for disaster management using emergency plans.
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Christopher W. Zobel. (2013). Analytically comparing disaster recovery following the 2012 derecho. In J. Geldermann and T. Müller S. Fortier F. F. T. Comes (Ed.), ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management (pp. 678–682). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: This work in progress paper discusses analytically characterizing nonlinear recovery behavior through the context of the derecho windstorm that struck the mid-Atlantic United States in the summer of 2012. The focus is on the recovery efforts of the Appalachian Power Company, and the discussion includes a look at the need for communicating the progress of such recovery efforts to the public. Publicly available recovery data is analyzed and compared with respect to the relative behaviors exhibited by two different nonlinear recovery processes, and some of the implications for understanding the efficiency of different disaster recovery operations are discussed.
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Daniel E. Lane, Tracey L. O'Sullivan, Craig E. Kuziemsky, Fikret Berkes, & Anthony Charles. (2013). A structured equation model of collaborative community response. In J. Geldermann and T. Müller S. Fortier F. F. T. Comes (Ed.), ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management (pp. 906–911). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: This paper analyses the collaborative dynamic of community in response to urgent situations. Community emergencies arising from natural or man-induced threats are considered as exogenous events that stimulate community resources to be unified around the response, action, and recovery activities related to the emergency. A structured equation model is derived to depict the actions of the community system. The system is described in terms of its resources including the propensity to trigger community action and collaboration among diverse groups. The community is profiled with respect to its ability to respond. The system defines the trigger mechanisms that are considered to be the drivers of collaborative action. A simulation model is presented to enact the system emergencies, community profiles, and collaborative response. The results develop an improved understanding of conditions that engage community collaborative actions as illustrated by examples from community research in the EnRiCH and the C-Change community research projects.
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Denis Barcaroli, Alex Coletti, Antonio De Nicola, Antonio Di Pietro, Luigi La Porta, Maurizio Pollino, et al. (2019). An Automatic Approach to Qualitative Risk Assessment in Metropolitan Areas. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: Risk assessment aims at improving prevention and preparedness phases of the crisis management lifecycle.
Qualitative risk assessment of a system is important for risks identification and analysis by the various stakeholders and often requires multi-disciplinary knowledge. We present an automatic approach to qualitative
risk assessment in metropolitan areas using semantic techniques. In particular, users are provided with a computational support to identify and prioritize by relevance risks of city services, through generation of
semantic descriptions of risk situations. This approach is enabled by a software system consisting of: TERMINUS, a domain ontology representing city knowledge; WS-CREAM, a web service implementing risk identification and ranking functions; and CIPCast, a GIS-based Decision Support System with functions of risk
forecast due to natural hazards. Finally we present the results of a preliminary validation of the generated risks concerning some points of interest in two different areas of the city of Rome.
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Diana Fischer, Carsten Schwemmer, & Kai Fischbach. (2018). Terror Management and Twitter: The Case of the 2016 Berlin Terrorist Attack. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 459–468). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: There is evidence that people increasingly use social networking sites like Twitter in the aftermath of terrorist attacks to make sense of the events at the collective level. This work-in-progress paper focuses on the content of Twitter messages related to the 2016 terrorist attack on the Berlin Christmas market. We chose topic modeling to investigate the Twitter data and the terror management theory perspective to understand why people used Twitter in the aftermath of the attack. In particular, by connecting people and providing a real-time communication channel, Twitter helps its users collectively negotiate their worldviews and re-establish self-esteem. We provide first results and discuss next steps.
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Dick Ooms, & Willem-Jan Van Den Heuvel. (2014). If every nail looks different, you need different hammers: Modeling civil-military interaction. In and P.C. Shih. L. Plotnick M. S. P. S.R. Hiltz (Ed.), ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management (pp. 349–353). University Park, PA: The Pennsylvania State University.
Abstract: In the response to emergencies and disasters, effective cooperation and information exchange between military and civil actors is essential. However, in practice, the quality of civil-military interaction (CMI) leaves much to be desired. Our research takes an engineering approach, which is complementary to most behavioral-oriented research in the CMI domain. In particular, we seek to support CMI processes with innovative Information Technology solutions. To this end, we are developing a comprehensive conceptual model of the CMI domain, which is currently lacking. This paper contributes to its development by investigating candidate technologies and defining CMI domain model requirements. Exploiting these requirements as criteria, we have evaluated three modeling methods and languages, i.e. the Unified Modeling Language (UML), the Business Process Modeling Notation (BPMN) and the Design and Engineering Methodology for Organizations (DEMO). Based on the comparative study, we conclude that a combination of these is required for modeling the CMI domain.
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Dick Ooms, Willem-Jan van den Heuvel, & Bartel Van de Walle. (2018). A Conceptual Framework for Civil-Military Interaction in Peace Support Operations. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 1003–1015). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: In complex emergencies, civil and military organizations often find themselves being partners in an international effort aimed at peace keeping, humanitarian relief, and development support. Civil and military partners need to exchange information and to cooperate as required. This assumes effective and efficient Civil-Military Interaction (CMI). However, CMI research literature shows that, in practice, this is far from a reality. In particular, our research indicates that deficiencies in knowledge processes and knowledge management within international civil and military organizations contribute to the causes of ineffective and inefficient CMI. Our research aims to investigate the feasibility of developing technical solutions exploiting knowledge engineering, to support fieldworkers in overcoming these CMI problems. As a first step, this paper introduces a Conceptual Framework (CF) that captures reference models of the CMI domain. The CF has been developed to analyze CMI problems and underlying KM deficiencies. It is being illustrated, explored and validated using real-world case studies.
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Duncan T. Wilson, Glenn I. Hawe, Graham Coates, & Roger S. Crouch. (2012). Estimating the value of casualty health information to optimization-based decision support in response to major incidents. 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: In this paper we describe a work-in-progress decision support program designed for use in the response to major incidents in the UK. The proposed program is designed for use in a continuous fashion, where the updating of its model, the search for solutions to the model through an optimization algorithm, and the issuing of these solutions are carried out concurrently. The model facilitates the inclusion of dynamic and uncertain features of emergency response. The potential of such an approach to deliver high-quality response plans through enabling more accurate modeling is evaluated through focusing on the case of casualty health information. Computational experiments show there is significant value in monitoring the dynamic and uncertain health progression of casualties and updating the model accordingly. © 2012 ISCRAM.
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Elio Rich. (2006). Modeling risk dynamics in e-operations transitions. In M. T. B. Van de Walle (Ed.), Proceedings of ISCRAM 2006 – 3rd International Conference on Information Systems for Crisis Response and Management (pp. 239–250). Newark, NJ: Royal Flemish Academy of Belgium.
Abstract: Migrations to new modes of operation are perilous times for most organizations. For firms that routinely work in high-threat, high-reward situations, the risks of innovation are particularly challenging. This paper presents a systems-based approach to understanding these risks, drawing examples from one firm migrating to e-Operations for offshore oil platforms to increase profitability. The firm recently participated in two facilitated group model building exercises to examine the effects of the migration on the organization and resources needed to safely implement multiple changes over time. Based on these exercises, a simulation model of the timing and relative levels of risk, was developed. The results of the workshop and simulation demonstrate the effect of a combined qualitative and quantitative modeling approach to understanding complex problems.
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Elisa Canzani. (2016). Modeling Dynamics of Disruptive Events for Impact Analysis in Networked Critical Infrastructures. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
Abstract: Governments have strongly recognized that the proper functioning of critical infrastructures (CIs) highly determines the societal welfare. If a failed infrastructure is unable to deliver services and products to the others, disruptive effects can cascade into the larger system of CIs. In turn, decision-makers need to understand causal interdependencies and nonlinear feedback behaviors underlying the entire CIs network toward more effective crisis response plans. This paper proposes a novel block building modeling approach based on System Dynamics (SD) to capture complex dynamics of CIs disruptions. We develop a SD model and apply it to hypothetical scenarios for simulation-based impact analysis of single and multiple disruptive events. With a special focus on temporal aspects of system resilience, we also demonstrate how the model can be used for dynamic resilience assessment. The model supports crisis managers in understanding scenarios of disruptions and forecasting their impacts to improve strategic planning in Critical Infrastructure Protection (CIP).
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Elisa Canzani, & Ulrike Lechner. (2015). Insights from Modeling Epidemics of Infectious Diseases ? A Literature Review. In L. Palen, M. Buscher, T. Comes, & A. Hughes (Eds.), ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management. Kristiansand, Norway: University of Agder (UiA).
Abstract: The relevance of modeling epidemics? spread goes beyond the academic. The mathematical understanding of infectious diseases has become an important tool in policy making. Our research interest is modeling of dynamics in crisis situations. This paper explores the extant body of literature of mathematical models in epidemiology, with particular emphasis on theories and methodologies used beyond them. Our goal is to identify core building blocks of models and research patterns to model the dynamics of crisis situations such as epidemics. The wide range of applications of epidemic models to many other disciplines that show biological analogies, makes this paper helpful for many modelers and mathematicians within the broader field of Crisis Management.
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Fabiana Santos Lima, Bernd Hellingrath, Adam Widera, & Mirian Buss Gonçalves. (2013). A systemic process model for procurement decisions in humanitarian logistics. In J. Geldermann and T. Müller S. Fortier F. F. T. Comes (Ed.), ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management (pp. 688–692). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: The relief organizations work in volatile environments involving a variety of actors with different skills and knowledge. The service of emergency for victims of natural disasters requires a rapid decision-making. The objective of the approach presented in this paper is to develop a Systemic Process Model (SPM) for procurement decisions in humanitarian logistics. The SPM aims to support procurement tasks of humanitarian organizations during the response phase in disaster relief. The approach provides a decision support tool using an appropriate quantitative model reflecting the specific area of humanitarian logistics processes.
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Flávio Horita, João Porto de Albuquerque, Victor Marchezini, & Eduardo M. Mendiondo,. (2016). A qualitative analysis of the early warning decision-making process in disaster management. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
Abstract: Early warning systems are an important means of improving the efficiency of disaster response and preparedness. However, in its analysis of the technological aspects of the infrastructure, the literature has failed to carry out an investigation of early warning process. This paper has sought to take a step toward understanding this issue by carrying out a qualitative analysis of the early warning process in disaster management. This has involved participatory observations and conducting interviews with practitioners from the National Center for Monitoring and Early Warning of Natural Disasters (CEMADEN). The results have shown that this research area is a promising way of increasing efficiency and reducing the response time to warnings. This might be achieved by conducting a process analysis, which could provide evidence and information about bottlenecks or investigate the misuse of information systems or tasks by the players involved.
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Frédérick Bénaben, Chihab Hanachi, Matthieu Lauras, Pierre Couget, & Vincent Chapurlat. (2008). A metamodel and its ontology to guide crisis characterization and its collaborative management. In B. V. de W. F. Fiedrich (Ed.), Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management (pp. 189–196). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: This paper presents a research in progress about the French ISyCri project that aims at providing partners involved in crisis management with an agile Mediation Information System (MIS). Not only this MIS shoul support the interoperability of the partners' information systems but it is also dedicated to coordinate their activities through a collaborative process. One of the first and main steps towards such a MIS, is to elaborate a common and sharable reference model built to characterize crisis situations. Such a model is also an input for automated reasoning to elaborate and adapt a crisis solving collaborative process. This article presents the objective of the project, our approach and our first results: a UML metamodel of crisis situation and its corresponding OWL ontology on top of which deductions are possible.
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Gaoussou Camara, Rim Djedidi, Sylvie Despres, & Moussa Lo. (2012). Towards an ontology for an epidemiological monitoring 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: Epidemiological monitoring systems are used to control the evolution of disease spreading and to suggest action plans to prevent identified risks. In this domain, risk prediction is based on quantitative approaches that are hardly usable when data collection is not possible. In this paper, a qualitative approach based on an epidemiological monitoring ontology is proposed. We describe the design of this ontology and show how it fits into classical monitoring systems and helps overcoming limits related to quantitative approaches. © 2012 ISCRAM.
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Gary M. Fetter, Mauro Falasca, Christopher W. Zobel, & Terry R. Rakes. (2010). A multi-stage decision model for debris disposal operations. 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: As shown by Hurricane Katrina, disposing of disaster-generated debris can be quite challenging. Extraordinary amounts of debris far exceeding typical annual amounts of solid waste are almost instantaneously deposited across a widespread area. Although the locations and amounts of debris can be easily summarized looking back after recovery activities have been completed, they are uncertain and difficult at best to estimate as debris operations begin to unfold. Further complicating matters is that the capacity of cleanup resources, which is dependent upon available equipment, labor, and subcontractors, can fluctuate during on-going cleanup operations. As a result, debris coordinators often modify initial resource assignments as more accurate debris estimates and more stable resource capacities become known. In this research, we develop a computer-based decision support system that incorporates a multi-stage programming model to assist decision makers with allocating debris cleanup resources immediately following a crisis event and during ongoing operations as debris volumes and resource capacities become known with increasing certainty.
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George Leventakis, Athanasios Sfetsos, Vasileios Gkrizis, Nikolas Athanasiadis, Stefan Tönjes, Spyros Kopsidas, et al. (2011). A Security Risk Analysis Framework for interconnected transportation systems. In E. Portela L. S. M.A. Santos (Ed.), 8th International Conference on Information Systems for Crisis Response and Management: From Early-Warning Systems to Preparedness and Training, ISCRAM 2011. Lisbon: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: The present paper introduces a comprehensive Transportation Security Risk Assessment Framework for assessing related risks and provides cohered contingency management procedures in interconnected, interdependent and heterogeneous transport networks. The proposed approach includes elements, methodological tools and approaches found in the literature, in addition to operational experience from the organization of major events.
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