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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Madhavi M. Chakrabarty, & David Mendonça. (2005). Design considerations for information systems to support critical infrastructure 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. 13–18). Brussels: Royal Flemish Academy of Belgium.
Abstract: This paper develops a set of design considerations for information systems to support the management of interdependent critical infrastructure systems. Constraints on how these systems are managed are oriented along technical, political and organizational dimensions, though objectives along these dimensions may conflict and thus be difficult to satisfy. This paper harnesses methodologies from software engineering and cognitive science in order to specify opportunities for using information systems to support human-centered management of critical infrastructure systems. The particular focus of this work is on developing information systems to support visualization and visual problem solving. Progress to date is discussed in terms of an ongoing research project which uses as a test-bed data associated with lower Manhattan (New York, USA).
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Changwon Son, Jukrin Moon, S. Camille Peres, & Farzan Sasangohar. (2018). An Episode as a Trace of Resilient Performance in Multi-Agency Incident Management Systems. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 942–948). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: In order to cope with increasing complexity of catastrophic disasters, resilience is considered an essential capability of an incident management system (IMS). As resilience is manifested during systems operation, a naturalistic observational study was conducted to understand how resilient performance dynamically takes place in this domain. The study results were presented using the concept of episodes, each of which uncovers a trace of such resilient performance following an information input called an inject. The episode analysis also facilitated the identification of complex and dynamic interactions among human and technological agents to satisfy work demands, representing work-as-done (WAD) in large-scale emergency response operations.
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Chanvi Kotak, Brian Tomaszewski, & Erik Golen. (2018). 3-1-1 Calls Hot Spot Analysis During Hurricane Harvey: Preliminary Results. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 350–361). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: Hurricane Harvey caused massive damage and necessitated the need for identification of areas under high risk. During Harvey, the city of Houston received more than 77000, 3-1-1 calls for assistance. Due to damage caused to the infrastructure, it became difficult to handle and respond to the crisis. Geographic Information Systems (GIS) is a vital technology to assist with real-time disaster monitoring. we investigated if a correlation could be found between 311 data calls made during the Hurricane Harvey and aerial images captured during the event, specifically to see if 311 data could be ground-truthed via hot spot analysis. Preliminary results indicate that visual representation of 3-1-1 call data can aid in analyzing the expected areas of high traffic of calls for assistance and plan an effective way to manage resources. Future work will involve more in-depth analysis of combined 3-1-1 call data with satellite imagery using image classification techniques.
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Christian Reuter, Gerhard Backfried, Marc-André Kaufhold, & Fabian Spahr. (2018). ISCRAM turns 15: A Trend Analysis of all ISCRAM-Papers 2004-2017. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 445–458). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: In 2004, Information Systems for Crisis Response and Management (ISCRAM) was a new area of research. Pioneering researchers from different continents and disciplines found fellowship at the first ISCRAM work-shop. Around the same time, the use of social media in crises was first recognized in academia. In 2018, the 15th ISCRAM conference will take place, which gives us the possibility to look back on what has already been achieved with regard to IT support in crises using social media. With this article, we examine trends and devel-opments with a specific focus on social media. We analyzed all papers published at previous ISCRAMs (n=1339). Our analysis shows that various platforms, the use of language and coverage of different types of disasters follow certain trends – most noticeably a dominance of Twitter, English and crises with large impacts such as hurricanes or earthquakes can be seen.
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Timothy Clark, & Rich Curran. (2013). Geospatial site suitability modeling for US department of defense humanitarian assistance projects. 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. 463–467). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: The purpose of this paper is to outline the requirement for data-driven methods for determining optimal geographic locations of United States Department of Defense (DOD) Humanitarian Assistance (HA) resources, including disaster mitigation and preparedness projects. HA project managers and tactical implementers charged with cost-efficient deployment of HA resources are challenged to produce measurable effects, in addition to contributing to broader Joint and Interagency-informed security assistance strategies. To address these issues, our ongoing research advocates geospatial multi-criteria site suitability decision support capabilities that leverage 1) existing geospatial resource location-allocation methodology as applied in government, retail, and commercial sectors; 2) user-generated criteria and objective preferences applied in widely-used decision frameworks; 3) assessments of the feasibility of obtaining data at a geographic scale where DOD tactical/operational level users can benefit from the model outputs; and 4) social science theory related to the HA domain criteria that form the foundation of potential decision models.
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Tina Comes, Frank Schätter, & Frank Schultmann. (2013). Building robust supply networks for effective and efficient disaster 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. 230–240). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: The effective and efficient distribution of relief goods is a key challenge in disaster management. Typically, adhoc supply networks (SNs) need to be built, in which various actors with different interests collaborate. Although information is sparse and highly uncertain, time for SN design is short, and important strategic decisions (e.g., location of facilities), whose revision requires investing substantial time, effort and resources, must be made promptly. This paper presents an iterative approach for the design of robust SNs that combines (i) an optimisation model to identify promising alternatives to be analysed in detail, (ii) a scenario-based approach to analyse the weaknesses of these alternatives and generate alternative solutions for comparison and benchmarking, and (iii) a decision support module for detailed comparisons and consensus building. By following the iterative approach, successively robust SNs are created to enable effective and efficient disaster response. We illustrate our approach by an example from the Haiti 2010 earthquake.
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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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Tina Comes, Michael Hiete, Niek Wijngaards, & Masja Kempen. (2009). Integrating scenario-based reasoning into multi-criteria decision analysis. 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: Multi-criteria decision analysis (MCDA) is a technique for decision support which aims at providing transparent and coherent support for complex decision situations taking into account subjective preferences of the decision makers. However, MCDA does not foresee an analysis of multiple plausible future developments of a given situation. In contrast, scenario-based reasoning (SBR) is frequently used to assess future developments on the longer term. The ability to discuss multiple plausible future developments provides a rationale for strategic plans and actions. Nevertheless, SBR lacks an in-depth performance evaluation of the considered actions. This paper explores the integration of both techniques that combines their respective strengths as well as their application in environmental crisis management. The proposed methodology is illustrated by an environmental incident example. Future work is to conduct validations on the basis of real-world scenarios by public Dutch and Danish chemical incident crisis management authorities.
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Congcong Wang, Paul Nulty, & David Lillis. (2021). Transformer-based Multi-task Learning for Disaster Tweet Categorisation. 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. 705–718). Blacksburg, VA (USA): Virginia Tech.
Abstract: Social media has enabled people to circulate information in a timely fashion, thus motivating people to post messages seeking help during crisis situations. These messages can contribute to the situational awareness of emergency responders, who have a need for them to be categorised according to information types (i.e. the type of aid services the messages are requesting). We introduce a transformer-based multi-task learning (MTL) technique for classifying information types and estimating the priority of these messages. We evaluate the effectiveness of our approach with a variety of metrics by submitting runs to the TREC Incident Streams (IS) track: a research initiative specifically designed for disaster tweet classification and prioritisation. The results demonstrate that our approach achieves competitive performance in most metrics as compared to other participating runs. Subsequently, we find that an ensemble approach combining disparate transformer encoders within our approach helps to improve the overall effectiveness to a significant extent, achieving state-of-the-art performance in almost every metric. We make the code publicly available so that our work can be reproduced and used as a baseline for the community for future work in this domain.
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Daniel Lichte, Dustin Witte, & Kai-Dietrich Wolf. (2020). Comprehensive Security Hazard Analysis for Transmission Systems. 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. 1145–1153). Blacksburg, VA (USA): Virginia Tech.
Abstract: Critical energy infrastructures are more and more focused upon by politics and society. Modern society depends on these structures, since they enable the steady support of electricity and other types of energy. Deliberately precipitated hazards of certain critical parts of electrical transmission systems (ETS) can lead to catastrophic consequences. Therefore, the analysis of feasible security hazards and resulting consequences for the operation of transmission systems are a concern to transmission system operators (TSO). Alas, there is no common method available that comprehensively identifies these feasible security related scenarios and classifies them according to their overall criticality for the safe operation of the ETS. To tackle this challenge, we propose a comprehensive, yet easy-to-apply method to systematically identify and assess the criticality of security threat scenarios. It is conducted in four steps and consists of a matrix based consistency check of threat scenarios in a defined solution space and a convenient semi-quantitative assessment of a risk factor for the ETS. The approach is illustrated by the simplified generic example of an EETS.
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Daniel Link, Bernd Hellingrath, & Jie Ling. (2016). A Human-is-the-Loop Approach for Semi-Automated Content Moderation. 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: Online social media has been recognized as a valuable information source for disaster management whose volume, velocity and variety exceed manual processing capacity. Current machine learning systems that support the processing of such data generally follow a human-in-the-loop approach, which has several inherent limitations. This work applies the human-is-the-loop concept from visual analytics to semi-automate a manual content moderation workflow, wherein human moderators take the dominant role. The workflow is instantiated with a supervised machine learning system that supports moderators with suggestions regarding the relevance and categorization of content. The instantiated workflow has been evaluated using in-depth interviews with practitioners and serious games. which suggest that it offers good compatibility with work practices in humanitarian assessment as well as improved moderation quality and higher flexibility than common approaches.
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David Paulus, Kenny Meesters, Gerdien de Vries, & Bartel Van de Walle. (2019). The reciprocity of data integration in disaster risk analysis. 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: Humanitarian organizations are increasingly challenged by the amount of data available to drive their decisions. Useful data can come from many sources, exists in different formats, and merging it into a basis for analysis and planning often exceeds organizations? capacities and resources. At the same time, affected communities? participation in decision making processes is often hindered by a lack of information and data literacy capacities within the communities. We describe a participatory disaster risk analysis project in the central Philippines where the community and a humanitarian NGO worked towards a joint understanding of disaster risks and coping capacities through data integration and IT-supported analysis. We present findings from workshops, focus group discussions and semi-structured interviews, showing the reciprocal effects of the collaborative work. While the community valued the systematically gathered and structured evidence that supported their own risk perceptions and advocacy efforts, the humanitarian NGO revisited established work practices for data collection for analysis and planning.
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Tiago C. De França, Diogo Nolasco, Rafael Lage Tavares, Jose Orlando Gomes, & De Paulo V. R. Carvalho. (2014). A critical insight of the pope's visit to Brazil for the world youth day: Resilience or fragility? 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. 463–472). University Park, PA: The Pennsylvania State University.
Abstract: This work proposes a model to evaluate systems regarding their resilience in handling unexpected disturbances. To exemplify the use of the proposed model, we chose to analyze the World Youth Day (WID), an important event on the global scenario that happened this year in Rio de Janeiro, a city which will host big events in the next few years, like the World Cup and the Olympic Games. From this event, we chose two disturbances that stressed the system and had the possibility to cause a lot of problems to the event and the city, like the rains in Guaratiba and the arrival of the Pope's committee. After analyzing how the overall WYD organization deal with these disturbances we conclude that, besides the success of the event, the organization showed much more signs of brittleness than resilience.
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Simone De Kleermaeker, & Jan Verkade. (2013). A decision support system for effective use of probability forecasts. 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. 290–295). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
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.
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Ur?ka Demsar, Olga Patenková, & Kirsi Virrantaus. (2007). Centrality measures and vulnerability of spatial networks. In K. Nieuwenhuis P. B. B. Van de Walle (Ed.), Intelligent Human Computer Systems for Crisis Response and Management, ISCRAM 2007 Academic Proceedings Papers (pp. 201–209). Delft: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Effective management of infrastructural networks in the case of a crisis requires a prior analysis of the vulnerability of spatial networks and identification of critical locations where an interdiction would cause most damage and disruption. This paper presents a preliminary study into how a graph theoretic structural analysis could be used for this purpose. Centrality measures are combined with a dual graph modelling approach in order to identify critical locations in a spatial network. The results of a case study on a street network of a small area in the city of Helsinki indicate that 'betweenness' is the most promising centrality measure for this purpose. Other measures and properties of graphs are under consideration for eventually developing a risk model not only for one but for a group of co-located spatial networks.
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Derya Ipek Eroglu, Duygu Pamukcu, Laura Szczyrba, & Yang Zhang. (2020). Analyzing and Contextualizing Social Vulnerability to Natural Disasters in Puerto Rico. 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. 389–395). Blacksburg, VA (USA): Virginia Tech.
Abstract: As the third hurricane the U.S. experienced in 2017, Hurricane María generated impacts that resulted in both short term and long term suffering in Puerto Rico. In this study, we aim to quantify the vulnerability of Puerto Ricans by taking region and society specific characteristics of the island into account. To do this, we follow Cutter et al.'s social vulnerability calculation, which is an inductive approach that aims to represent a society based on its characteristics. We adapted the Social Vulnerability Index (SoVI) for Puerto Rico by using data obtained from the U.S. Census Bureau. We analyzed the newly calculated SoVI for Puerto Rico and compared it with the existing deductive approach developed by the Center for Disease Control (CDC). Our findings show that the new index is able to capture some characteristics that the existing vulnerability index is unable to do.
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André Dittrich, & Christian Lucas. (2013). A step towards real-time analysis of major disaster events based on tweets. 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. 868–874). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: The most popular micro blogging platform Twitter has been the topic of a variety of research papers related to disaster and crisis management. As an essential first step and basis for a real-time methodology to exploit Twitter for event detection, localization and ultimately semantic content analysis, a functional model to describe the amount of tweets during a day has been developed. It was derived from a corpus of messages in an exemplary area of investigation. To satisfy the different daily behavior on particular days, two types of days are distinguished in this paper. Moreover, keyword-adjusted data is used to point out the potential of semantic tweet analysis in following steps. The consideration of spatial event descriptions in relevant tweets could significantly improve and accelerate the perception of a disaster. The results from the conducted tests demonstrate the capability of the functional model to detect events with significant social impact in Twitter data.
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Geneviève Dubé, Chelsea Kramer, François Vachon, & Sébastien Tremblay. (2011). Measuring the impact of a collaborative planning support system on crisis management. 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: Crisis management (CM) is an aspect of command and control characterized by complexity, uncertainty, and severe time pressure. To address these challenges, CM teams can use collaborative work support systems (CWSS) to help plan their intervention and coordination activities. However, the use of CWSS is not necessarily beneficial and in some cases, can impede more than augment performance. Hence, it is essential to understand the impact of a CWSS on team performance and CM teamwork. We have developed a methodology to assess the effectiveness of CWSS by comparing the use of an interactive Smartboard with that of a traditional topographic map during team planning activities. To do so, a dynamic CM situation is simulated using a forest firefighting functional simulation – the C3Fire microworld. We compared two groups of participants on the basis of performance, communication, coordination efficiency, and planning quality. Based on a preliminary analysis, in comparison to maps, the use of a CWSS seems to be beneficial to planning activities and CM coordination. At this point the main contribution of the current on-going project is to provide a method and metrics for the objective assessment of new technology in the context of CM.
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Tom Duffy, Chris Baber, & Neville Stanton. (2013). Measuring collaborative sensemaking. 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. 561–565). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: Problems of collaborative sensemaking are evident in major incident response where sharing salient information is key to the shared understanding of the situation. In this paper we propose that differences in sensemaking performance can be captured through quantitative methods derived from consideration of network structure and information diffusion as the group collaborates to achieve consensus in a problem-solving task. We present analysis from a large international study in which groups of people collaborate to solve an intelligence analysis problem. Our initial analysis suggests that 'edge' groups are able to collaborate more efficiently and perform better than those which have a hierarchical control structure.
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Duygu Pamukcu, Christopher Zobel, & Yue Ge. (2022). A Data Envelopment Analysis-based Approach for Managing Performance of Public Service Systems During a Disaster. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 144–153). Tarbes, France.
Abstract: In addition to their normal task of supporting community participation, engagement, and improved information access, information technology-based public service systems are also essential for maintaining critical services and providing effective communication with citizens before, during, and after emergencies. This study focuses on the impacts of disaster events on the operational performance of such service systems and discusses opportunities for managing service efficiency by rearranging and reallocating resources during emergencies. To the best of our knowledge, this is the first attempt to provide a practical method for improving the relative efficiency of public service systems in such a context. We suggest a Data Envelopment Analysis (DEA) approach for quantifying the relative efficiencies associated with service requests from an input-output-based standpoint, and discuss the Orange County (Florida) 311 non-emergency service system, in the context of the COVID-19 pandemic, as an example of how such operational efficiency can be managed during a disruption.
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Sukumar Dwarkanath, & Michael Daconta. (2006). Emergency services enterprise framework: A service-oriented approach. In M. T. B. Van de Walle (Ed.), Proceedings of ISCRAM 2006 – 3rd International Conference on Information Systems for Crisis Response and Management (pp. 298–304). Newark, NJ: Royal Flemish Academy of Belgium.
Abstract: The current Emergency Services landscape is characterized by a number of systems and networks that are isolated in nature, thus making information sharing impractical, if not impossible. Such an environment does not promote ease of information sharing, and each incident highlights the need for efficient collaboration and coordination, and the need for a holistic internetwork-a series of virtual interconnected networks-approach. In other words, it requires an overall framework that looks at safety as an overall enterprise, (albeit one with thousands of independent agency owners), with the strategic goal to facilitate greater collaboration and effectiveness of operations, and to ensure a streamlined and efficient prevention of, response to, and recovery from all-hazards. 1 Adopting a Service-Oriented enterprise approach is extremely useful and has number of advantages in such an environment. This paper defines a framework-in the context of an enterprise-an envisioned Emergency Services Enterprise Framework, and identifies the key elements of this framework.
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Sukumar Dwarkanath, & Denis Gusty. (2010). Information sharing: A strategic approach. 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: The purpose of this paper is to provide and recommend a strategic approach for implementation of information sharing initiatives. While such an approach offers a number of benefits, as a primary benefit, it provides a way to measure and monitor the performance of such initiatives, irrespective of their scope, whether they are regional, state, or federal efforts. The first section of the paper presents a framework for alignment among information sharing initiatives; the second section builds on this framework and outlines a roadmap for an assessment methodology for such initiatives.
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Edjossan-Sossou, A., Selouane, K., Sayah, M. A., Ouabou, M., Vignote, C., Capitaine, M., et al. (2023). An innovative scenario-based modeling tool for the management of resilient water resources. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 808–821). Omaha, USA: University of Nebraska at Omaha.
Abstract: As freshwater availability for domestic and agro-industrial uses is highly sensitive to climate change, there is an urgent need for the management of this critical resource to be resilient, i.e., to cope with and rapidly recover from climate risks. To achieve this resilient goal, decision-makers need to have a comprehensive understanding of (i) the current and future local water resources, (ii) the ways these resources are and will be impacted by climate change, and (iii) the effects their management decisions can have. In this paper, we present an innovative scenario based modeling tool that help decision-makers make the most appropriate decision towards managing water resources: the Resilience Performance Assessment (RPA). This GIS-based decision support tool illustrates the current and future effects of climate change on local water resources and simulates the outcomes of different water resources management strategies. The RPA helps guide decision-makers towards the implementation of context specific adaptation strategies.
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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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