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Andrea H. Tapia, Nicklaus A. Giacobe, Nicolas LaLone, & Pamela J. Soule. (2015). Scaling 911 Messaging for Emergency Operation Centers During Large Scale Events. 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: In this paper we imagine that one day soon, mass crisis events will result in thousands of people trying to get emergency help multiple via multiple mediums. Public Access Service Points and 911 Centers will not be able to meet the demand of text-message calls for help during a large scale disaster. While 911 dispatchers will need to respond directly to each individual text message, we present the development and testing of a system that aims to provide this data, in real-time, directly to emergency managers during a large-scale crisis. The system is designed to accept, sort, triage and deliver hundreds of direct text messages from the PSAP and provide them directly to emergency management staff, who can leverage their content. In the hands of the emergency manager, these data can be used to inform resource allocation decisions, enhance their operational situational awareness, and potentially improve the response to the crisis.
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Andrés Moreno, Philip Garrison, & Karthik Bhat. (2017). WhatsApp for Monitoring and Response during Critical Events: Aggie in the Ghana 2016 Election. 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. 645–655). Albi, France: Iscram.
Abstract: Mobile Instant Messaging platforms like WhatsApp are becoming increasingly popular. They have expanded access to digital text, audio, picture, and video messaging. Integrating them into existing crisis monitoring and response platforms and workflows can help reach a wider population. This paper describes a first attempt to integrate WhatsApp into Aggie, a social media aggregating and monitoring platform. We report on the deployment of this integration during Ghana's 2016 election, along with Twitter, Facebook, and RSS. The WhatsApp messages collected by Aggie during the election improved the eectiveness of the monitoring eorts. Thanks to these messages, more incidents were found and escalated to the Electoral Commission and security forces. From interviews with people involved in monitoring and response, we found that the WhatsApp integration helped their coordination and monitoring activities.
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Andrew Arnette, Christopher W. Zobel, & Duygu Pamukcu. (2020). Post-Impact Analysis of Disaster Relief Resource Pre-Positioning After the 2013 Colorado Floods. 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. 237–243). Blacksburg, VA (USA): Virginia Tech.
Abstract: Pre-positioning of supplies is important to facilitate disaster relief operations, however it is only after a disaster event occurs that the effectiveness of the pre-positioning strategy can be properly assessed. With this in mind, this paper analyzes a risk-based pre-positioning algorithm, developed for the American Red Cross, in the context of its actual performance in the 2013 Colorado Front Range floods. The paper assesses the relative effectiveness of the pre-positioning approach with respect to historical asset placements, and it discusses changes to the model that are necessary to support such comparisons and allow for further model extensions.
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Anjum, U., Zadorozhny, V., & Krishnamurthy, P. (2023). Localization of Events Using Neural Networks in Twitter Data. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 909–919). Omaha, USA: University of Nebraska at Omaha.
Abstract: In this paper, we develop a model with neural networks to localize events using microblogging data. Localization is the task of finding the location of an event and can be done by discovering event signatures in microblogging data. We use the deep learning methodology of Bi-directional Long Short-Term Memory (Bi-LSTM) to learn event signatures. We propose a methodology for labeling the Twitter date for use in Bi-LSTM However, there might not be enough data available to train the Bi-LSTM and learn the event signatures. Hence, the data is augmented using generative adversarial networks (GAN). Finally, we combine event signatures at different temporal and spatial granularity to improve the accuracy of event localization. We use microblogging data collected from Twitter to evaluate our model and compare it with other baseline methods.
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Anmol Haque, Duygu Pamukcu, Ruixiang Xie, Mohsen Zaker Esteghamati, Margaret Cowell, & Jennifer L. Irish. (2021). Cascading Effects of Mass Gatherings on COVID-19 Infections from a Multi-hazard Perspective: A Case Study of New York City. 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. 218–227). Blacksburg, VA (USA): Virginia Tech.
Abstract: The devastating economic and societal impacts of COVID-19 can be substantially compounded by other secondary events that increase individuals' exposure through mass gatherings such as protests or sheltering due to a natural disaster. Based on the Crichton's Risk Triangle model, this paper proposes a Markov Chain Monte Carlo (MCMC) simulation framework to estimate the impact of mass gatherings on COVID-19 infections by adjusting levels of exposure and vulnerability. To this end, a case study of New York City is considered, at which the impact of mass gathering at public shelters due to a hypothetical hurricane will be studied. The simulation results will be discussed in the context of determining effective policies for reducing the impact of multi-hazard generalizability of our approach to other secondary events that can cause mass gatherings during a pandemic will also be discussed.
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Anna Kruspe, Jens Kersten, & Friederike Klan. (2019). Detecting event-related tweets by example using few-shot models. 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: Social media sources can be helpful in crisis situations, but discovering relevant messages is not trivial. Methods
have so far focused on universal detection models for all kinds of crises or for certain crisis types (e.g. floods).
Event-specific models could implement a more focused search area, but collecting data and training new models for
a crisis that is already in progress is costly and may take too much time for a prompt response. As a compromise,
manually collecting a small amount of example messages is feasible. Few-shot models can generalize to unseen
classes with such a small handful of examples, and do not need be trained anew for each event. We show how
these models can be used to detect crisis-relevant tweets during new events with just 10 to 100 examples and
counterexamples. We also propose a new type of few-shot model that does not require counterexamples.
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Anne-Marie Barthe-Delanoë, Sébastien Truptil, Nelly Olivier-Maget, & Frédérick Bénaben. (2018). Towards an Organizational and Socio-Technical Context-Aware Adaptation of Emergency Plans. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 212–217). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: In France, facilities listed under environment protection regulations are required to draw up emergency plans. During a crisis situation, facing an unexpected event, these plans may be irrelevant. They have to be adapted to the current crisis situation and its observed or anticipated evolutions, using data emitted by the crisis ecosystem. But this adaptation requires lots of effort and is time-consuming. This article aims at presenting an approach to ensure the dynamic adaptation of emergency plans. We propose to identify generic configuration variables (representing interactions of physical phenomena and human factors on the facility) and to feed these configuration variables by collecting and processing data emitted by sensors, social networks, official reports, etc. Therefore, emergency plans could natively integrate agility by their ability to detect and take into account a change in the crisis situation and decision makers will be supported since the early stage of the crisis response.
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Anton Björnqvist, Marc Friberg, Carl-Oscar Jonson, Jenny Pettersson, & Peter Berggren. (2022). An Analysis of a Swedish Medical Command and Control System’s Situation Reports from the COVID-19 Pandemic. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 334–348). Tarbes, France.
Abstract: This paper presents an analysis of situation reports used and created by a crisis management team within the Swedish healthcare sector during the early phase of the COVID-19 pandemic. The analysis was conducted through a deductive content analysis, where categories were identified based on the concepts of common operational pictures, sensemaking, and situation awareness. In the analysis, support for all identified categories was found. Based on the analysis and the concepts, future recommendations regarding what type of information that ought to be included in situation reports were created. These recommendations include, amongst others, the categories of consequences, how it is perceived by the public, objectives, status and implications of information, future scenarios, actions, resources, and work procedures.
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Antone Evans Jr., Yingyuan Yang, & Sunshin Lee. (2021). Towards Predicting COVID-19 Trends: Feature Engineering on Social Media Responses. 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. 792–807). Blacksburg, VA (USA): Virginia Tech.
Abstract: During the course of this pandemic, the use of social media and virtual networks has been at an all-time high. Individuals have used social media to express their thoughts on matters related to this pandemic. It is difficult to predict current trends based on historic case data because trends are more connected to social activities which can lead to the spread of coronavirus. So, it's important for us to derive meaningful information from social media as it is widely used. Therefore, we grouped tweets by common keywords, found correlations between keywords and daily COVID-19 statistics and built predictive modeling. The features correlation analysis was very effective, so trends were predicted very well. A RMSE score of 0.0425504, MAE of 0.03295105 and RSQ of 0.5237014 in relation to daily deaths. In addition, we found a RMSE score of 0.07346836, MAE of 0.0491152 and RSQ 0.374529 in relation to daily cases.
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Antonin Segault, Federico Tajariol, & Ioan Roxin. (2015). #geiger : Radiation Monitoring Twitter Bots for Nuclear Post-Accident Situations. 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: In the last decade, people have increasingly relied on social media platforms such as Twitter to share information on the response to a natural or a man-made disaster. This paper focuses on the aftermath of the Fukushima Daiichi nuclear disaster. Since the disaster, victims and volunteers have been sharing relevant information about radiation measurements by means of social media. The aim of this research is to explore the diffusion of information produced and shared by Twitter bots, to understand the degree of popularity of these sources and to check if these bots deliver original radiation measurements.
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Antonin Segault, Federico Tajariol, Yang Ishigaki, & Ioan Roxin. (2016). #geiger 2: Developing Guidelines for Radiation Measurements Sharing on Social Media. 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: Radiation measurements are key information in post-nuclear accident situations. Automated Twitter accounts have been used to share the readings, but often in an incomplete way from the perspective of data sharing and risk communication between citizen and radiation experts. In this paper, we investigate the requirements for radiation measurements completeness, by analyzing the perceived usefulness of several metadata items that may go along the measurement itself. We carried out a benchmark of existing uses, and conducted a survey with both experts and lay citizens. We thus produced a set of guidelines regarding the metadata that should be used, and the way to publish it.
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Antonio De Nicola, Maria Luisa Villani, Francesco Costantino, Andrea Falegnami, & Riccardo Patriarca. (2021). Knowledge Fusion for Distributed Situational Awareness driven by the WAx Conceptual Framework. 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. 79–85). Blacksburg, VA (USA): Virginia Tech.
Abstract: Large crisis scenarios involve several actors, acting at the blunt-end of the process, such as rescue team directors, and at the sharp-end, such as firefighters. All of them have different perspectives on the crisis situation, which could be either coherent, alternative or complementary. This heterogeneity of perceptions hinders situational awareness, which is defined as the achievement of an overall picture on the above-mentioned crisis situation. We define knowledge fusion as the process of integrating multiple knowledge entities to produce actionable knowledge, which is consistent, accurate, and useful for the purpose of the analysis. Hence, we present a conceptual modelling approach to gather and integrate knowledge related to large crisis scenarios from locally-distributed sources that can make it actionable. The approach builds on the WAx framework for cyber-socio-technical systems and aims at classifying and coping with the different knowledge entities generated by the involved operators. The conceptual outcomes of the approach are then discussed in terms of open research challenges for knowledge fusion in crisis scenarios.
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Apoorva Chauhan, & Amanda Hughes. (2021). COVID-19 Named Resources on Facebook, Twitter, and Reddit. 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. 679–690). Blacksburg, VA (USA): Virginia Tech.
Abstract: Crisis Named Resources (CNRs) are social media accounts and pages named after a crisis event. They are created soon after an event occurs. CNRs share a lot of information around an event and are followed by many. In this study, we identify CNRs created around COVID-19 on Facebook, Twitter, and Reddit. We analyze when these resources were created, why they were created, how they were received by members of the public, and who created them. We conclude by comparing CNRs created around COVID-19 with past crisis events and discuss how CNR owners attempt to manage content and combat misinformation.
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Ummul Khair Israt Ara, & Fang Chen. (2012). Information security in crisis management 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: Information security is an important part of almost any kind of Information System. Crisis Management Systems (CMS) are a type of Information System that deals with information which needs to be secure. No matter what kind of crisis, natural disasters, man-made crisis or terrorist attacks, the CMS security should not be compromised. There are many challenges regarding exchange of qualified information and interoperability between various Expert Systems and the CMS. It is important to have strong security in terms of technology, skills, security requirements, sensitivity of information and trust-worthiness (Vural, Ciftcibasi and Inan, 2010). Depending on the type of crisis situation, different sets of security components should be triggered, since the security requirements vary between situations. For example, a terrorist attack has different security requirements in the system compared to a natural disaster or a medical emergency. In this paper, the importance of Information Security in CMS will be discussed. Methods for secure exchange of qualified information are analyzed and a secure and dynamic Crisis Management Information Security System (CMISS) design is introduced. © 2012 ISCRAM.
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Laura Ardila, Israel Perez-Llopis, Carlos E. Palau, & Manuel Esteve. (2013). Virtual reality training environment for strategic and tactical emergency operations. 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. 140–144). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: The application of Information and Communication Technologies in emergency management environments is a challenging research topic; particularly, the applicability of C4ISR (Command, Control, Communications, Computers, Intelligence, Surveillance and Reconnaissance) systems specifically designed for these environments. A key aspect in emergency management is the training of operatives at all levels, from intervention to operational, including tactical command and control. Virtual reality is widely used for training and learning purposes, but the interaction of real and virtual worlds with new standards (i.e. MPEG-V), going a step further from the traditional approach to create virtual environments based in expensive simulation dedicated equipment and allowing data streaming between both worlds, has not yet been exploited in training for emergency management. This paper proposes an architecture for a C4ISR training system providing interoperability between real and virtual worlds using the MPEG-V standard and allowing simultaneous and real time training of both real and virtual units.
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Richard Arias-Hernandez, & Brian Fisher. (2013). An interaction approach to enhance situational awareness and the production of anticipatory actions in emergency operation centers. 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. 488–496). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: Recent findings from fieldwork conducted at emergency operation centers (EOC) suggest that currently deployed emergency management information systems (EMIS) are not supporting properly the anticipation of individual actions in cooperative work. We present these findings in this paper and introduce joint action theory as an interaction approach to design technologies that explicitly provide for this kind of support. Our main arguments are: (1) contemporary EMIS are affecting negatively cooperative work at EOCs due to their lack of support for the anticipation of individual actions; (2) Available theory that emphasizes the role of anticipation on cooperative work is not impacting on the design of EMIS due to misalignments between the theory and contemporary situations; (3) Joint action theory provides an alternative framework to correct these misalignments; and (4) Joint action theory provides designers of EMIS with guides for an interaction design that supports anticipatory actions in EOCs.
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Arjen Schmidt, Jeroen Wolbers, Kees Boersma, Julie Ferguson, & Peter Groenwegen. (2016). Are you Ready2Help? Dilemmas in organizing citizen response to disaster. 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: Over the last decade, the disaster response landscape is increasingly complemented by voluntary citizen initiatives on digital platforms. These developments have opened up opportunities for response agencies and NGOs to organize local community involvement. In this paper we focus on the question how citizen involvement can be proactively organized toward disaster relief and what kind of dilemmas may arise in this process. We studied Ready2Help, an online platform developed by the Dutch Red Cross. Bringing together 36.000 volunteers, the platform plays a significant role in addressing the current refugee crisis. In our analysis we demonstrate the platform?s potential, but also note a tension between control and cooperation. Our results indicate that, in contrast to their initial objective, during the crisis the Red Cross falls back on principles of control to organize citizen response efforts. We end by discussing our future research agenda aimed at bridging formal and emergent citizen responses.
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Gaston C. Armour, & Hero Tameling. (2011). Collaborative relationships are key to community resilience and emergency preparedness. 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 United States of America experienced two major incidents that changed the countrys perspective on emergency preparedness: September 11, 2001 World Trade Center attacks, and Hurricane Katrina in 2005. Since that time the United States Department of Homeland Security established 10 separate Regional Catastrophic Planning Teams (RCPT) around the country. These RCPTs were set-up to inform, train and determine the effectiveness of mutual-aid coordination and prepare individuals, families and communities for an “all-hazard” environment. As RCPT members representing one state agency providing human services, the authors proposed an initiative, based on a working model they had already deployed in their own agency, to enhance emergency preparedness activities to include individual and community resiliency along with disaster and catastrophic planning. That request to expand the RCPT role, opened-up a dialogue to develop an innovative approach to collaborative partnerships. This shift afforded additional opportunities in times of a crisis, disaster or catastrophe.
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Arnis Parsovs. (2020). Solving the Estonian ID Card Crisis: the Legal Issues. 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. 459–471). Blacksburg, VA (USA): Virginia Tech.
Abstract: In 2017, Estonia experienced a cyber crisis caused by a vulnerability found in the smart card chips produced by Infineon Technologies AG. Since the affected chip was used in the electronic identity card (ID card) issued by the State to more than half of the Estonian population, the vulnerability posed a risk to the resilience of Estonian e-state and thus quickly escalated into a manageable crisis. This work studies to what extent, in such a national emergency, the involved parties were able to precisely follow the applicable laws and regulations in the field. We enlist the cases where the requirements were not fully followed, either due to the lack of technical preparedness, suboptimal decisions made under heavy time pressure, or the critical nature of the situation.
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Naveen Ashish, & Sharad Mehrotra. (2010). Community driven data integration for emergency response. 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 describes our work in progress on an approach and technology for providing integrated data access in situational awareness applications – particularly for disaster and emergency response. The key new aspect of our work is an approach where information aggregation, processing, and integration capabilities are offered as a service to any new application builder. Further, we provide a framework for possibly reusing prior information integration knowledge, the development of which demands the major fraction of time and complexity in a new application, in a customized fashion for new application. Our overall goal is to provide a framework where integrated access to critical data in an emergency response situation can be enabled very rapidly and by personnel with basic IT and data handling expertise. Our approach, while general purpose, is currently motivated by and grounded in the context of situational awareness systems for incident commander decision support in the fire response domain.
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Mikael Asplund, Trishan R. De Lanerolle, Christopher Fei, Prasanna Gautam, Ralph A. Morelli, Simin Nadjm-Tehrani, et al. (2010). Wireless ad hoc dissemination for search and rescue. 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: In search and rescue scenarios local information on victims and other finds needs to be disseminated rapidly to other rescue workers and team leaders. However, post disaster scenarios may imply the collapse of information infrastructure including cellular communication and Internet connectivity. Even if we consider wireless ad hoc communication as a means of information dissemination we should count on frequent loss of connectivity in the network due to unpredictable mobility and sparse network topologies. In this paper we present the realization of an existing manycast protocol (random walk gossip) on commodity handheld devices running the Android platform. This communication mode is used to demonstrate the potential for distributed information dissemination on victims and finds. The application layer is an adaptation of an existing surveying information tool (POSIT) which is now fully decentralized and relies on text communication to achieve energy efficiency.
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Christoph Aubrecht, Klaus Steinnocher, & Hermann Huber. (2014). DynaPop – Population distribution dynamics as basis for social impact evaluation in crisis management. 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. 314–318). University Park, PA: The Pennsylvania State University.
Abstract: In this paper ongoing developments regarding the conceptual setup and subsequent implementation logic of a seamless spatio-temporal population dynamics model are presented. The DynaPop model aims at serving as basic input for social impact evaluation in crisis management. In addition to providing the starting point for assessing population exposure dynamics, i.e. the location and number of affected people at different stages during an event, knowledge of spatio-temporal population distribution patterns is also considered crucial for a set of other related aspects in disaster risk and crisis management including evacuation planning and casualty assessment. DynaPop is implemented via a gridded spatial disaggregation approach and integrates previous efforts on spatio-temporal modeling that account for various aspects of population dynamics such as human mobility and activity patterns that are particularly relevant in picturing the highly dynamic daytime situation.
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Audrey Fertier, Aurélie Montarnal, Anne-Marie Barthe-Delanoë, Sébastien Truptil, & Frédérick Bénaben. (2016). Adoption of Big Data in Crisis 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: Most agree that the innate complexity and uncertainty of a crisis compel the stakeholders to coordinate in a hurry, despite their heterogeneity or the volume of data to process. Supporting their coordination is now possible, thanks to a mediation system combined with big data management tools. The GéNéPi1 project explores this possibility and proposes to improve the generation of collaborative processes offered by the MISE2?s solution. The idea is to increase the number of usable data sources. To do that, in a fixed time-frame, the situation models have to be instantly generated upon sets of raw data. This new methodology holds the key to a new big data era: an age where global understanding reigns.
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Audrey Fertier, Aurélie Montarnal, Sébastien Truptil, Anne-Marie Barthe-Delanoë, & Frédérick Bénaben. (2017). A situation model to support collaboration and decision-making inside crisis cells, in real time. 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. 1020–1028). Albi, France: Iscram.
Abstract: Natural and man-made hazards have many unexpected consequences that concern as many heterogeneous services. The GéNéPi project offers to support officials in addressing those events: its purpose is to support the collaboration in the field and the decision-making in the crisis cells. To succeed, the GéNéPi system needs to be aware of the ongoing crisis developments. For now, its best chance is to benefit from the ever growing number of available data sources. One of its goals is, therefore, to learn how to manage numerous, heterogeneous, more or less reliable data, in order to interpret them, in time, for the officials. The result consists on a situation model in the shape of a common operational picture. This paper describes every stage of modelling from the raw data selection, to the use of the situation model itself.
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Audun Stolpe, & Jo Hannay. (2021). On the Adaptive Delegation and Sequencing of Actions. 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. 28–39). Blacksburg, VA (USA): Virginia Tech.
Abstract: Information systems support to crisis response and management relies crucially on presenting actionable information in a manner that supports cognitive processes, and does not overwhelm them. We outline how AI Planning can be used viably to support the \emph{delegation and sequencing} of tasks. The idea is to use standard operating procedures as initial specifications of plans in terms of actors, actions and delegation rules. When expressed in the AI planning language \textit{Answer set Programming} (ASP), machine reasoning can be used in a \textit{pre-incident review} to display relevant delegation and sequencing inherent in a plan. % together with measures of goal achievement. The purpose of this is to uncover weaknesses in the initial plan and to optimize sequencing and delegation to increase the likelihood of achieving goals. Further, adaptive planning can be supported in \textit{during-incident reviews} by updating the current status, upon which ASP will then compute new alternatives. % and corresponding goal achievement measures. At this point, initial goals may no longer be viable and the explicit suggestion of prior sub-optimal goals now worth pursuing can be a game-changer under stress. The conceptual basis we lay out in terms of delegation and sequencing can be readily extended with further planning factors, such as resource requirements, role transfer and goal achievement.
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