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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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Dashley K. Rouwendal van Schijndel, Jo E. Hannay, & Audun Stolpe. (2020). Simulation Vignette Generation from Answer Set Specifications. 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. 110–121). Blacksburg, VA (USA): Virginia Tech.
Abstract: We investigate an approach that allows exercise managers to design simulations with an explicit focus on building skills, rather than having to focus on all the objects and interactions that a simulation must have. Exercise managers may design exercises at various levels of abstraction and always independently of how those sessions are implemented in simulations, while simulation components that implement the design are assembled and to some extent, automatically, behind the scenes. We outline (1) how Answer Set Programming can assist exercise managers in exercise planning and (2) how automated stage and content generation may be used to invoke appropriate simulation components to realize the design. For deliberate and recurrent training of decision-making skills, stages and content must vary to avoid familiarity (testing effects). We conclude by distilling a main research hypothesis that stipulates how (1) and (2) represent two modes of automated reasoning (so-called deductive versus abductive) and how that distinction clarifies the planning task.
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Debora Robles Perez, Manuel Esteve Domingo, Israel Perez Llopis, & Federico J. Carvajal Rodrigo. (2020). System and Architecture of an Adapted Situation Awareness Tool for First Responders. 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. 928–936). Blacksburg, VA (USA): Virginia Tech.
Abstract: First responders (FRs) in Europe are currently facing large natural and man-made disasters (e.g. wild fire, terrorist attacks, industrial incidents, big floods, gas leaks etc.), that put their own lives and those of thousands of others at risk. Adapted situation awareneSS tools and taIlored training curricula for increaSing capabiliTies and enhANcing the proteCtion of first respondErs (ASSISTANCE) is an ongoing European H2020 project which main objective is to increase FRs Situation Awareness (SA) for helping and protecting different kinds of FRs' organizations that work together in large scale disasters mitigation. ASSISTANCE will enhance the SA of the FRs organisations during their mitigation activities through the integration of new paradigms, tools and technologies (e.g. drones/robots equipped with a range of sensors, robust communications capabilities, etc.) with the main objective of increasing both their protection and their efficiency.
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Deena Disraelly, & Laura Itle. (2020). Providing Reliable Assistance Faster: Secure, Modern, Mission-Capable Credentialing to Support Disaster Operations. 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. 1140–1143). Blacksburg, VA (USA): Virginia Tech.
Abstract: The public sector, including state and local government, public health, and emergency management; the private sector; and the Federal Government jointly face challenges with rapidly collecting and validating credentials for individuals applying for employment or volunteering for emergencies, vetting security clearances, and ascertaining suitability. In 2017, for instance, credentialing gaps delayed employees and volunteers from contributing much-needed skills in disaster areas during one of the worst hurricane and wildfire seasons on record while Federal agencies inadvertently issued interim clearances to individuals with criminal records. We propose a secure, modern, mission-capable information technology solution to these with the United States Postal Service hosting this streamlined process by serving as the hub for collection, validation, and transfer of pertinent data. The solution would introduce access points in over 5,000 communities for citizens participating in disaster support operations, as well as those requiring credentialing for employment as part of day-to-day operations.
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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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Dipak Singh, Shayan Shams, Joohyun Kim, Seung-jong Park, & Seungwon Yang. (2020). Fighting for Information Credibility: AnEnd-to-End Framework to Identify FakeNews during Natural Disasters. 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. 90–99). Blacksburg, VA (USA): Virginia Tech.
Abstract: Fast-spreading fake news has become an epidemic in the post-truth world of politics, the stock market, or even during natural disasters. A large amount of unverified information may reach a vast audience quickly via social media. The effect of misinformation (false) and disinformation (deliberately false) is more severe during the critical time of natural disasters such as flooding, hurricanes, or earthquakes. This can lead to disruptions in rescue missions and recovery activities, costing human lives and delaying the time needed for affected communities to return to normal. In this paper, we designed a comprehensive framework which is capable of developing a training set and trains a deep learning model for detecting fake news events occurring during disasters. Our proposed framework includes infrastructure to collect Twitter posts which spread false information. In our model implementation, we utilized the Transfer Learning scheme to transfer knowledge gained from a large and general fake news dataset to relatively smaller fake news events occurring during disasters as a means of overcoming the limited size of our training dataset. Our detection model was able to achieve an accuracy of 91.47\% and F1 score of 90.89 when it was trained with the first 28 hours of Twitter data. Our vision for this study is to help emergency managers during disaster response with our framework so that they may perform their rescue and recovery actions effectively and efficiently without being distracted by false information.
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Duygu Pamukcu, Christopher W. Zobel, & Andrew Arnette. (2020). Characterizing Social Community Structures in Emergency Shelter Planning. 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. 228–236). Blacksburg, VA (USA): Virginia Tech.
Abstract: During emergencies, it is often necessary to evacuate vulnerable people to safer places to reduce loss of lives and cope with human suffering. Shelters are publically available places to evacuate, especially for people who do not have any other choices. This paper overviews emergency shelter planning in disaster mitigation and preparation and discusses the need for better responding to people who need to evacuate during emergencies. Recent evacuation studies pay attention to integrating social factors into evacuation modeling for better prediction of evacuation decisions. Our goal is to address the impact of social behavior on the sheltering choices of evacuees and to explore the potential contributions of including social network characteristics in the decision-making process of authorities. We present the shelter utilization problem in South Carolina during Hurricane Florence and discuss an agent-based modeling approach that considers social community structures in modeling the shelter choice behavior of socially connected individuals.
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Edward J. Glantz, Frank E. Ritter, Don Gilbreath, Sarah J. Stager, Alexandra Anton, & Rahul Emani. (2020). UAV Use in Disaster Management. 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. 914–921). Blacksburg, VA (USA): Virginia Tech.
Abstract: Unmanned aerial vehicles (UAV) provide multiple opportunities to first responders and disaster managers, especially as they continue to improve in affordability as well as capabilities. This paper provides a brief review of how UAV capabilities have been used in disaster management, examples of current use within disaster management, as well as adoption considerations. Example disaster domains include fires, tornadoes, flooding, building and dam collapses, crowd monitoring, search and rescue, and post disaster monitoring of critical infrastructures. This review can increase awareness and issues when considering UAVs by those challenged with the management of crisis and disaster events.
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Eric Rigaud, Anouck Adrot, Frank Fiedrich, Nour Kanaan, Miriam Klein, Farnaz Mahdavian, et al. (2020). Borderland Resilience Studies. 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. 338–355). Blacksburg, VA (USA): Virginia Tech.
Abstract: This article describes the definition and characteristics of borderland resilience studies as an academic field, and precisely its core phenomenon, major themes or components and challenges. The phenomenon of borderland resilience is firstly defined. The results of empirical studies complete the conceptual description. Finally, the article proposes a set of research and development challenges.
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Erik AM Borglund, & Martina Granholm. (2020). You Talk the Talk – But What Do You Talk About? 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. 295–302). Blacksburg, VA (USA): Virginia Tech.
Abstract: Post-crisis analysis of transboundary crises in Sweden is problematic due to limited documentation. We believe that there is a need to find tools to better understand the command and control, and to understand how the information sharing that takes place during larger crises works. This paper presents the results of an ongoing research, as well as findings about how the TETRA system is used for information sharing in transboundary crises. The data used was collected from two large emergency exercises, where Swedish, Finnish and Norwegian TETRA systems were merged. Communication in 10 shared talk groups was recorded, transcribed and analyzed. The communication in shared TETRA-talk-groups mostly focused on information about the accident, the recourses and first respond units, as well as the actions of each unit. The research also exemplifies and shows that communication within TETRA-talk-groups in transboundary crisis can give new insight into how command and control works.
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Erik Prytz, Anna-Maria Grönbäck, Krisjanis Steins, Craig Goolsby, Tobias Andersson Granberg, & Carl-Oscar Jonson. (2020). Evaluating the Effect of Bleeding Control Kit Locations for a Mass Casualty Incident Using Discrete Event Simulation. 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. 167–178). Blacksburg, VA (USA): Virginia Tech.
Abstract: The purpose of this study was to develop a simulation model to evaluate bleeding control kit location strategies for a mass casualty incident scenario. Specifically, the event simulated was an explosion at a large sports arena. The model included a representation of the arena itself, simulated crowd movements following the detonation of an improvised explosive device, injuries and treatments, and different ways for immediate responders to help injured patients using tourniquets. The simulation model gave logically consistent results in the validation scenarios and the simulation outcomes were in line with the expected outcomes. The results of the different tourniquet location scenarios indicated that decentralized placement (more than one location) is better, easy access is important (between rather than at emergency exits) and that an increased number of available tourniquets will result in an increased number of survivors.
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Eva Petitdemange, Elyes Lamine, Franck Fontanili, & Matthieu Lauras. (2020). Enhancing Emergency Call Centers' Performance Through a Data-driven Simulation Approach. 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. 218–227). Blacksburg, VA (USA): Virginia Tech.
Abstract: Emergency Call Centers (ECCs) can be considered as the starting point of the pre-hospital emergency medical system. Although, ECCs exist everywhere, their business processes and their performance levels differ from one place to another, even sometimes in a same country. By definition, users expect a high level of performance, particularly regarding the waiting time and the processing time of the calls. Additionally, ECCs might have difficulties to manage sudden rise of activities following disasters impacting huge number of victims for instance. To support ECCs in their continuous improvement steps, this paper suggests an innovative framework and its associated tools to support both diagnosis of current organizations and enhancement of their performance. Concretely, the proposal is data-driven and simulation oriented. First experiments are shown in order to demonstrate the potential benefits of such an approach. Avenues for further research are also discussed.
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Ferda Ofli, Firoj Alam, & Muhammad Imran. (2020). Analysis of Social Media Data using Multimodal Deep Learning for Disaster Response. 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. 802–811). Blacksburg, VA (USA): Virginia Tech.
Abstract: Multimedia content in social media platforms provides significant information during disaster events. The types of information shared include reports of injured or deceased people, infrastructure damage, and missing or found people, among others. Although many studies have shown the usefulness of both text and image content for disaster response purposes, the research has been mostly focused on analyzing only the text modality in the past. In this paper, we propose to use both text and image modalities of social media data to learn a joint representation using state-of-the-art deep learning techniques. Specifically, we utilize convolutional neural networks to define a multimodal deep learning architecture with a modality-agnostic shared representation. Extensive experiments on real-world disaster datasets show that the proposed multimodal architecture yields better performance than models trained using a single modality (e.g., either text or image).
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Flavio Dusse, Renato Novais, & Manoel Mendonça. (2020). A Visual Analytics Based Model for Crisis Management Decision-Making. 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. 157–166). Blacksburg, VA (USA): Virginia Tech.
Abstract: Crisis Management (CM) refers to the ability to deal with crisis tasks in different phases and iterations. People working in a crisis are generally under pressure to make the right decision at the right time. They must process large amounts of data and assimilate the received information in an intuitive way. Visual Analytics (VA) is potentially useful to analyze and understand the huge amount of data in several areas including in a crisis. We propose a model based on VA to support decision-making in CM. The aim of the model is to help visualization designers to create effective VA interfaces, to help crisis managers to make quick and assertive decisions with them. In previous studies, we carried out a survey protocol with a multi-method approach to collect data on crisis related decision-making and analyze all these data qualitatively with formal techniques during the large events held in Brazil in recent years. In this work, we used our previous findings to develop the proposed model. We validated it using the focus group technique. With the new findings, we identified relevant insights on the use of VA for crisis management. We hope that, with these continuous cycles of validation and improvement, the agencies that manage crises might use our model as a reference for building more effective IT decision-making infrastructures based on VA.
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Frederick Benaben, & Lysiane Benaben. (2020). Science Fiction: Past and Future Trends of Crisis Management. 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. 1130–1139). Blacksburg, VA (USA): Virginia Tech.
Abstract: This paper is a position paper, presenting an original but very anticipative and mainly imaginative vision of the evolution of the crisis management domain. After analyzing the options to make the past evolutions of that domain somehow explainable (mainly by analyzing the data of all the articles of the last fifteen editions of the ISCRAM conference), the paper aims at providing a framework to assess and evaluate the maturity of the domain of crisis management. Moreover, this framework is also used to tentatively infer some future evolutions and some directions that could be relevant, dangerous, tricky or of great benefit for the crisis management domain. These future trends are mainly based on the current maturity of crisis management (according to the proposed framework) and current or future influential practices, technologies or threats. It will be necessary to wait for fifteen years to see if these bets should be considered as accurate.
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Gerasimos Antzoulatos, Panagiotis Giannakeris, Ilias Koulalis, Anastasios Karakostas, Stefanos Vrochidis, & Ioannis Kompatsiaris. (2020). A Multi-Layer Fusion Approach For Real-Time Fire Severity Assessment Based on Multimedia Incidents. 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. 75–89). Blacksburg, VA (USA): Virginia Tech.
Abstract: Shock forest fires have short and long-terms devastating impact on the sustainable management and viability of natural, cultural and residential environments, the local and regional economies and societies. Thus, the utilisation of risk-based decision support systems which encapsulate the technological achievements in Geographical Information Systems (GIS) and fire growth simulation models have rapidly increased in the last decades. On the other hand, the rise of image and video capturing technology, the usage mobile and wearable devices, and the availability of large amounts of multimedia in social media or other online repositories has increased the interest in the image understanding domain. Recent computer vision techniques endeavour to solve several societal problems with security and safety domains to be one of the most serious amongst others. Out of the millions of images that exist online in social media or news articles a great deal of them might include the existence of a crisis or emergency event. In this work, we propose a Multi-Layer Fusion framework, for Real-Time Fire Severity Assessment, based on knowledge extracted from the analysis of Fire Multimedia Incidents. Our approach consists of two levels: (a) an Early Fusion level, in which state-of-the-art image understanding techniques are deployed so as to discover fire incidents and objects from images, and (b) the Decision Fusion level which combines multiple fire incident reports aiming to assess the severity of the ongoing fire event. We evaluate our image understanding techniques in a collection of public fire image databases, and generate simulated incidents and feed them to our Decision Fusion level so as to showcase our method's applicability.
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Giulio Palomba, Alessandro Farasin, & Claudio Rossi. (2020). Sentinel-1 Flood Delineation with Supervised Machine Learning. 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. 1072–1083). Blacksburg, VA (USA): Virginia Tech.
Abstract: Floods are one of the major natural hazards in terms of affected people and economic damages. The increasing and often uncontrolled urban sprawl together with climate change effects will make future floods more frequent and impacting. An accurate flood mapping is of paramount importance in order to update hazard and risk maps and to plan prevention measures. In this paper, we propose the use of a supervised machine learning approach for flood delineation from satellite data. We train and evaluate the proposed algorithm using Sentinel-1 acquisition and certified flood delineation maps produced by the Copernicus Emergency Management Service across different geographical regions in Europe, achieving increased performances against previously proposed supervised machine learning approaches for flood mapping.
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Haiyan Hao, & Yan Wang. (2020). Hurricane Damage Assessment with Multi-, Crowd-Sourced Image Data: A Case Study of Hurricane Irma in the City of Miami. 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. 825–837). Blacksburg, VA (USA): Virginia Tech.
Abstract: The massive crowdsourced data generated on social networking platforms (e.g. Twitter and Flickr) provide free, real-time data for damage assessment (DA) even during catastrophes. Recent studies leveraging crowdsourced data for DA mainly focused on analyzing textual formats. Crowdsourced images can provide rich and objective information about damage conditions, however, are rarely researched for DA purposes. The highly-varied content and loosely-defined damage forms make it difficult to process and analyze the crowdsourced images. To address this problem, we propose a data-driven DA method based on multi-, crowd-sourced images, which includes five machine learning classifiers organized in a hierarchical structure. The method is validated with a case study investigating the damage condition of the City of Miami caused by Hurricane Irma. The outcome is then compared with a metric derived from NFIP insurance claims data. The proposed method offers a resource for rapid DA that supplements conventional DA methods.
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Hannah Van Wyk, & Kate Starbird. (2020). Analyzing Social Media Data to Understand How Disaster-Affected Individuals Adapt to Disaster-Related Telecommunications Disruptions. 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. 704–717). Blacksburg, VA (USA): Virginia Tech.
Abstract: Information is a critical need during disasters such as hurricanes. Increasingly, people are relying upon cellular and internet-based technology to communicate that information--modalities that are acutely vulnerable to the disruptions to telecommunication infrastructure that are common during disasters. Focusing on Hurricane Maria (2017) and its long-term impacts on Puerto Rico, this research examines how people affected by severe and sustained disruptions to telecommunications services adapt to those disruptions. Leveraging social media trace data as a window into the real-time activities of people who were actively adapting, we use a primarily qualitative approach to identify and characterize how people changed their telecommunications practices and routines--and especially how they changed their locations--to access Wi-Fi and cellular service in the weeks and months after the hurricane. These findings have implications for researchers seeking to better understand human responses to disasters and responders seeking to identify strategies to support affected populations.
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Hanne Haaland, Hege Wallevik, Erika Frydenlund, & Jose J. Padilla. (2020). Modelers and Ethnographers as Co-Creators of Knowledge: Do We Belong Together? 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. 1113–1121). Blacksburg, VA (USA): Virginia Tech.
Abstract: In this paper, we explore the process of co-creation of knowledge between modelers and ethnographers through a project focusing on the role played by CIGS (Citizen initiatives for global solidarity) in the refugee crisis in the island of Lesvos, Greece. We describe the process of collaboration and discuss what this type of interdisciplinary collaboration may bring to the development of a research topic when the initial skepticism and questions of epistemological differences have been overcome. Moreover, we address some of the challenges embedded in this type of research collaboration, particularly the skepticism present within the social sciences.
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Harrison Cole. (2020). Accessible Mitigation Planning: Tactile Hazard Map Design and Evaluation. 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. 1031–1037). Blacksburg, VA (USA): Virginia Tech.
Abstract: While creating a community hazard mitigation plan (HMP) has become recognized as a key component of successful disaster management, significant portions of the process are often inaccessible to people with vision disabilities. Maps in particular are often large, visually dense documents that are printed on two-dimensional paper, or distributed via PDF with no alternate text. For people with profound low vision or who are blind, alternative media is required. The research discussed here proposes that tactile maps may present an accessible and cost-effective medium for representing geospatial data relevant to the hazard mitigation planning process. Using flood insurance rate maps (FIRMs) distributed by the Federal Emergency Management Agency (FEMA) as a starting point, this paper proposes an evaluatory framework for transcribing conventional maps into tactile documents, as well as characterizing users' experiences using them for mitigation planning, directions for future research and generalizing the process for applications in other domains.
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Henrique Romano Correia, Ivison da Costa Rubim, Angelica F.S. Dias, Juliana B.S. França, & Marcos R.S. Borges. (2020). Drones to the Rescue: A Support Solution for Emergency Response. 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. 904–913). Blacksburg, VA (USA): Virginia Tech.
Abstract: Emergency is a threatening condition that requires urgent action, an effective response and within an emergency scenario there may be risks for responders, as well as for those affected. Response time is crucial for affected individuals and environments to be addressed on their needs. In this context, the goal of this work is to support the agents involved in the emergency response, through an application-supported collaborative solution using drones. This solution aims to collect information from the worked emergency scenario, so that, through the collaboration of specialists, there is a greater support for the decision-making made by the responsible agents within this scenario, causing it to occur in a shorter time, thus speeding up the response to the emergency. In this work, the aim was to validate with experts from the Rio de Janeiro Firefighters, who already work with drones, by evaluating the utility of the solution in real scenarios.
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Henry Agsten. (2020). Effects of Smartphone-Based Alerting on Reducing Arrival Times for Volunteer Fire Departments. 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. 990–994). Blacksburg, VA (USA): Virginia Tech.
Abstract: This practitioner paper describes the efforts of a volunteer fire department in Germany to reduce the time to arrive at a place of emergency. It presents the former situation, identifies reasons for delays and highlights the volunteers' first years in utilizing an existing smartphone application for alert and response as a mean to optimize their times of arrival. The paper finally evaluates the effects of the application's usage.
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Hussain A. Syed, Marén Schorch, & Volkmar Pipek. (2020). Disaster Learning Aid: A Chatbot Centric Approach for Improved Organizational Disaster Resilience. 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. 448–457). Blacksburg, VA (USA): Virginia Tech.
Abstract: The increasingly frequent occurrence of organizational crises exemplifies the need to strengthen organizational resilience. An example of business organizations is small and medium enterprises (SMEs) which contribute largely to the economic growth. But often, their limited resources (manpower, time, financial capital), organizational structure, focus on operational routines and less priority towards disaster resilience make them more vulnerable to crisis than bigger companies. The proposed solution addresses this dilemma by establishing a collaborative medium within the organization to improve disaster resilience by raising awareness and self-learning in employees without overburdening their constrained routines and resources. Our work in progress demonstrates a conceptual model of a learning aid (collaboration channel and a chatbot) that supports the pedagogical methodologies and employs them for enhancing learnability and awareness and elaborates the usability of interactive learning instilling disaster resilience in employees and hence in an organization.
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James A. Reep, & Andrea Tapia. (2020). Toward an Organizational Technology Adoption Process (OTAP) for Social Media Integration in a PSAP. 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. 718–729). Blacksburg, VA (USA): Virginia Tech.
Abstract: Integration of social media in emergency response environments presents specific organizational challenges, such as lack of resources or information credibility. Additionally, there exists individual resistance to change in these environments that could potentially discourage adoption. To identify and understand these challenges, we conducted semi-structured group interviews with emergency call takers and dispatchers. We find that these PSAP operators desire participation and explanation of changes throughout the organizational change process. Participants also articulated they desired training regarding change even when not directly affected. Though change management procedures often call for these strategies, they are commonly overlooked, leaving individuals to imagine worse case scenarios that manifest as additional stress in an already stressful work environment. It is suggested that a formalized change management process which directly addresses the identified challenges within the organizational technology adoption process (OTAP) is needed in order to mitigate undue stress.
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