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José H. Canós-Cerdá, Carmen Penadés, Carlos Solís, Marcos R. S. Borges, & Manuel Llavador. (2010). Using spatial hypertext to visualize composite knowledge in emergency responses. 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: Having the right information at the right time is crucial to make decisions during emergency responses. To fulfill this requirement, emergency management systems must provide emergency managers with knowledge management and visualization tools. The goal is twofold: on one hand, to organize knowledge coming from different sources, mainly the emergency response plans (the formal knowledge) and the information extracted from the emergency development (the contextual knowledge); on the other hand, to enable effective access to information. Formal and contextual knowledge sets are mostly disjoint; however, there are cases in which a formal knowledge piece may be updated with some contextual information, constituting what we call the composite knowledge. In this paper, we extend a knowledge framework with the notion of composite knowledge, and use spatial hypertext to visualize this type of knowledge. We illustrate our proposal with a case study on accessing to information during an emergency response in an underground transportation system.
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Cendrella Chahine, François Peres, Thierry Vidal, & Mohamad El Falou. (2022). Functional and Dysfunctional Modelling and Assessment of an Emergency Response Plan. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 363–375). Tarbes, France.
Abstract: The objective of crisis management is to limit the impact of a feared event that has occurred and to restore the conditions corresponding to a nominal situation. In this context, we will focus on emergency response plans for mass casualty crises. In this paper, we propose a functional modelling of the French generic emergency plan, ORSEC plan, using the Business Process Model and Notation (BPMN). On the basis of this representation, a dysfunctional analysis is performed from a new approach identifying Failure mode, effects and criticality analysis (FMECA), in order to better anticipate, the events likely to interrupt the intervention plan. This work will then be used in a multi-agent dynamic planning and scheduling model to allow an actor to choose among the dynamic planning approaches the one that allows him/her to reach his/her goal.
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Fatemeh Hendijani Fard, Cooper Davies, & Frank Mauer. (2017). Agile Emergency Responses Using Collaborative Planning HTN. In eds Aurélie Montarnal Matthieu Lauras Chihab Hanachi F. B. Tina Comes (Ed.), Proceedings of the 14th International Conference on Information Systems for Crisis Response And Management (pp. 857–867). Albi, France: Iscram.
Abstract: Emergency response planning is a complex task due to multiple organizations involved, different planning considerations, etc. Using artificial intelligence collaborative planning helps in the automatic planning for complex situations. Analyzing all impacting factors along with plans that are executable can facilitate the decision making in Emergency Operations Centers for an agile emergency response. A main component of a planner is a knowledge base. Although many systems are developed to support decision making in emergency response or recovery, they either focus on specific or small organizations, or rely on simulations. To the best of our knowledge, there is a gap that there is no common knowledge base for provincial level mass emergencies for automatic planners. The multiplicity of the emergency response documents and their structure makes the knowledge acquisition complex. In this paper, we explain the process of extracting knowledge based on hierarchical task networks and how it speeds up the reactivity to a disaster.
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Norman Groner, & Charles Jennings. (2012). Describing pipeline emergency response communications using situational awareness informational requirements and an informational flow analyses. 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: The Christian Regenhard Center for Emergency Response Studies at John Jay College, CUNY, has begun work on developing best practices for hazardous material pipeline emergency response plans. The approach involves modeling a generic goal-based interagency emergency communications system using a two-step process. First, a situational awareness information requirements analysis will describe the informational requirements essential to an effective emergency response. The requirements analysis involves a goal decomposition approach where the information requirements are related to actionable decisions, goals and emergency response roles. Second, an information flow analysis will informational sources and means to provide required information. The same panel of experts will complete both analyses. Once the communications system is described, a separate Delphi group will use a failure modes and effects analysis (FMEA) to estimate the criticality of the components described in the situational awareness requirements and information flow analyses. © 2012 ISCRAM.
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Hoang Nam Ho, Mourad Rabah, Ronan Champagnat, & Frédéric Bretrand. (2019). Towards an Automatic Assistance in Crisis Resolution with Process Mining. 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: To deal with a crisis situation, experts must undertake a chain of activities, called process, to minimize crisis
consequences. To assist the expert in making decision in crisis resolutions, authors propose a method aiming at
discovering crisis response processes. This method is based on a two-step strategy: the first step classifies the
system?s traces, representing stakeholders? past actions, into different sets, where each one represents a set of
response processes according to a specific context; the second step uses process mining algorithm to discover
the corresponding response plan process model based on the obtained chain of activities for each previously
classified context. These response plans will be a referenced aid for experts while making crisis resolution,
according to each context. The proposed approach is illustrated on the traces issued from the crisis caused by the
2010 Xynthia storm in France.
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Kimmo Laakso. (2013). Emergency management: Identifying problem domains in communication. 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. 724–729). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: In emergency management, the identification of hazards, analysis of risks, development of mitigation and response plans, maintaining of situational awareness and support of response and recovery are all complex responsibilities. A major accident brings together individuals belonging to many different organizations, having backgrounds in different fields of operation, and representing different organizational cultures. They have to absorb a large amount of information about the accident over a short period of time. In order to take effective action, actors are expected to work smoothly together, thus the flow of information from and to the actors involved is crucial. Nevertheless, there are certain problem domains in the different phases of emergency management, which may weaken the flow of information. In this paper we present the findings of the first round of a Delphi study in which we identified problem domains in communication both in long-term and short-term planning for major accidents.
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Norbert Steigenberger. (2015). Organizing for the Big One ? A Review of Case Studies on Multi – Agency D isa s- ter Response and a Research Agenda. 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: Disaster response operations exceed the capacities of each single organization
Disaster response operations exceed the capacities of each single organization and thus require cooperation by at least two, often up to some hundred agencies who do seldom interact in their daily operations. The result is a complex problem of cognition, coordination, command and control. This paper presents a review of empirical studies on multi-agency coordination in disaster response operations in order to initiate and facilitate cross-case learning. The review covers 72 empirical studies and highlights the importance of themes such as plans and plan enactment, leadership or personal acquaintance of actors in emergent multi-agency response networks. The analysis also shows that while some themes received extensive coverage in scholarly publications (e.g. training, skills), various important topics have not been studied in sufficient depth (e.g. development of common operational pictures, plan enactment). Based on these insights, the review develops a research agenda and derives various recommendations for practical disaster response management.
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André Sabino, & Armanda Rodrigues. (2011). Understanding the role of cooperation in emergency plan construction. 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: In this paper we describe a proposal for information organization for computer supported cooperative work, while working with spatial information. It is focused on emergency response plan construction, and the requirements extracted from that task. At the centre of our proposal is the analysis of the structure of the cooperative workspace. We argue that the internal information representation should follow a spatial approach, tying the structure used to manage users with the structure used to manage information, suggesting the use of different spaces to represent the information. The gain we expect from this approach is the improved capacity to extract information on how people are cooperating and their relationship with the information they are working with. The ideas are introduced while focusing on real life emergency planning activities, where we discuss the current shortcomings of the cooperation strategies in use and propose a solution.
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Tobias Andersson Granberg, Carl-Oscar Jonson, Erik Prytz, Krisjanis Steins, & Martin Waldemarsson. (2020). Sensor Requirements for Logistics Analysis of Emergency Incident Sites. 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. 952–960). Blacksburg, VA (USA): Virginia Tech.
Abstract: Using sensors to collect data at emergency incident sites can facilitate analysis of the logistic operations. This can be used to improve planning and preparedness for new operations. Furthermore, real-time information from the sensors can serve as operational decision support. In this work in progress, we investigate the requirements on the sensors, and on the sensor data, to facilitate such an analysis. Through observations of exercises, the potential of using sensors for data collection is explored, and the requirements are considered. The results show that the potential benefits are significant, especially for tracking patients, and understanding the interaction between the response actors. However, the sensors need to be quite advanced in order to capture the necessary data.
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