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Yannic Schulte, Miriam Klein, Marcus Wiens, & Frank Fiedrich. (2020). Spontaneous Volunteers Across National Borders: An Agent-Based Comparison. 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. 327–336). Blacksburg, VA (USA): Virginia Tech.
Abstract: In today's globalized world and with the extensive use of social media, there is a high connectivity of people across countries, which can be a helpful potential in disaster response. In a coordinated manner, spontaneous volunteers from neighbouring nations can provide high manpower and resources to a disaster affected area. In this article, we discuss why the consideration of spontaneous volunteers is relevant in a cross-border context in order to improve disaster resilience for borderlands. Furthermore, we introduce a baseline agent-based model to simulate cooperation procedures for the involvement of spontaneous volunteers to the official crisis response in a borderland and discuss important issues that need to be addressed in future considerations.
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Yangyang Meng, Xiangliang Tian, Chang Liu, Zhongwen Li, Zhijie Zhou, & Maohua Zhong. (2020). Research on Emergency Capability Evaluation of Network Operation-Based Urban Rail Transit. 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. 530–544). Blacksburg, VA (USA): Virginia Tech.
Abstract: In the process of network operation, it is of great significance to evaluate the emergency capability for the safety and resilience of urban rail transit. In this work, we proposed an emergency capability evaluation model of network operation-based urban rail transit by building a four-level index system. AHP (Analytic Hierarchy Process) method demonstrated the effectiveness of the evaluation index system. The ranking of index importance Wi characterizes the emergency capability of network operation-based urban rail transit. Taking Shenzhen Metro as an example, this study analyzed the risk in the actual network operation, evaluated the emergency capability of network operation and calculated the comprehensive score of emergency capability. Furthermore, based on the correlation analysis results from the emergency capability indexes, we put forward some measures to improve the weaker indexes in the evaluation. The results indicate that the emergency capability evaluation method of network operation-based urban rail transit proposed in this study can better guide the emergency management of network operation-based urban rail transit.
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Xukun Li, & Doina Caragea. (2020). Improving Disaster-related Tweet Classification with a Multimodal 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. 893–902). Blacksburg, VA (USA): Virginia Tech.
Abstract: Social media data analysis is important for disaster management. Lots of prior studies have focused on classifying a tweet based on its text or based on its images, independently, even if the tweet contains both text and images. Under the assumptions that text and images may contain complementary information, it is of interest to construct classifiers that make use of both modalities of the tweet. Towards this goal, we propose a multimodal classification model which aggregates text and image information. Our study aims to provide insights into the benefits obtained by combining text and images, and to understand what type of modality is more informative with respect to disaster tweet classification. Experimental results show that both text and image classification can be improved by the multimodal approach.
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Xinyuan Zhang, & Nan Li. (2020). Assessment of the Correlation between Extreme Weather Event-Induced Human Mobility Perturbation in Urban Areas and their Spatial Characteristics based on Taxi Trajectories. 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. 366–380). Blacksburg, VA (USA): Virginia Tech.
Abstract: Extreme weather events (EWEs) are significant threats to urban regions. One major reflection of such impact is the EWE-induced perturbation to urban human mobility, which has been documented in a number of recent studies. This study aims to examine the spatial distribution of such perturbation within a city among different areas that are characterized by the type of function and the distance to city center. A case study was conducted on a major rainstorm in the City of Nanjing, China in 2017, based on trajectories of all taxis in the city before and during the rainstorm. It was found that the rainstorm caused decrease in people's travel demand throughout the city, although the magnitude of perturbation and level of resilience notably differed among areas of different functional types. In addition, the urban mobility in areas distant from the city center were relatively less influenced by the rainstorm.
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Xiaoyan Zhang, Graham Coates, Sarah Dunn, & Jean Hall. (2020). Emergency Evacuation from a Multi-floor Building using Agent-based Modeling. 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. 188–199). Blacksburg, VA (USA): Virginia Tech.
Abstract: This paper presents an overview of the ongoing research into the development of an agent-based model to enable simulations to be performed of agents evacuating from a multi-floor building with a complex layout, including staircases. Specifically, a flow field of navigation objects is constructed pre-computation, which stores the directions and shortest distances to all exits and staircases. Using the flow field, a navigation method is proposed for agents familiar with the environment to identify and follow the shortest route to a chosen exit. Preliminary simulations have been performed to investigate the effect on evacuation time of (i) exit configurations and (ii) familiarity of agents with the building layout. In assessing the effect of exit configurations, results show that the location of the main entrance has a significant influence on evacuation time. In addition, having more exits does not necessarily lead to a shorter evacuation time. In terms of the effect of familiarity of agents, having more agents with a greater level of familiarity does not significantly reduce evacuation time in most cases.
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Valerio Lorini, Javier Rando, Diego Saez-Trumper, & Carlos Castillo. (2020). Uneven Coverage of Natural Disasters in Wikipedia: The Case of 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. 688–703). Blacksburg, VA (USA): Virginia Tech.
Abstract: The usage of non-authoritative data for disaster management provides timely information that might not be available through other means. Wikipedia, a collaboratively-produced encyclopedia, includes in-depth information about many natural disasters, and its editors are particularly good at adding information in real-time as a crisis unfolds. In this study, we focus on the most comprehensive version of Wikipedia, the English one. Wikipedia offers good coverage of disasters, particularly those having a large number of fatalities. However, by performing automatic content analysis at a global scale, we also show how the coverage of floods in Wikipedia is skewed towards rich, English-speaking countries, in particular the US and Canada. We also note how coverage of floods in countries with the lowest income is substantially lower than the coverage of floods in middle-income countries. These results have implications for analysts and systems using Wikipedia as an information source about disasters.
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Toshihiro Osaragi. (2020). Accessibility Evaluation of Specific Emergency Transportation Roads and Benefits of Seismic Retrofits on Buildings Adjoining Roads. 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. 143–156). Blacksburg, VA (USA): Virginia Tech.
Abstract: Securing the accessibility of emergency vehicles using specific emergency transportation road (SETR) is crucial for the rapid activities of emergency vehicles after a large earthquake. In this paper, we construct a simulation model that describes collapse of roadside buildings and following street blockages, and evaluate the accessibility of emergency vehicles. Performing the simulations, we demonstrate the effects of quake-resistant-conversion of roadside buildings as follows: (1) the accessibility of emergency vehicles using SETR is not good enough under the current situation, but (2) can be significantly improved by performing seismic retrofit of buildings according to seismic index of building structure.
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Tomasz Opach, Jan Ketil Rød, Bjørn Erik Munkvold, Jaziar Radianti, Kristine Steen-Tveit, & Lars Ole Grottenberg. (2020). Map-based Interfaces for Common Operational Picture. 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. 506–516). Blacksburg, VA (USA): Virginia Tech.
Abstract: Common operational picture (COP) map-based interfaces display operational information to support integration of emergency responders. Such interfaces integrate different subsystems and present the resulting information into an overview for enabling situation awareness. Literature shows that they are often developed from non-user-centric perspectives and are defined in technological terms that are not adequately capturing the users' needs. Therefore, the aim of this particular work in progress is to get insight into the features and the role of COP map-based interfaces currently being used in Norway to (1) examine their content, functionality, and design; and (2) to understand how such displays are incorporated into the service context. This study structures the knowledge on map displays that constitute part of the COP services. Using workshop and interviews with the developers and users of existing COP map services, we identify requirements for a common operational symbology and common operational functionality to improve such map services and make them interoperable.
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Tomasz Opach, Carlo Navarra, Jan Ketil Rød, & Tina - Simone Neset. (2020). Towards a Route Planner Supporting Pedestrian Navigation in Hazard Exposed Urban Areas. 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. 517–528). Blacksburg, VA (USA): Virginia Tech.
Abstract: This study aims to design a route planner functionality that includes real-time context information from physical sensors and citizen observations to support pedestrian navigation in urban areas exposed to extreme heat and floods. Urban population is growing and people living in urban areas are especially exposed to heat and urban flooding, which are two of the anticipated effects of climate change. Route planning functionality can be of value to individual citizens, especially those with limited mobility, as well as for healthcare professionals and authorities who are responsible for crisis response and management. Although the route planner functionality is to be experimentally implemented in a specific tool with the use of broadly available web technologies and real time data, a major generic outcome is the framework that can be used to develop the functionality as part of a decision support tool of any kind.
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Tobias Andersson Granberg, Carl-Oscar Jonson, Erik Prytz, Krisjanis Steins, & Martin Waldemarsson. (2020). Sensor Requirements for Logistics Analysis of Emergency Incident Sites. In Amanda Hughes, Fiona McNeill, & Christopher W. Zobel (Eds.), ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management (pp. 952–960). Blacksburg, VA (USA): Virginia Tech.
Abstract: Using sensors to collect data at emergency incident sites can facilitate analysis of the logistic operations. This can be used to improve planning and preparedness for new operations. Furthermore, real-time information from the sensors can serve as operational decision support. In this work in progress, we investigate the requirements on the sensors, and on the sensor data, to facilitate such an analysis. Through observations of exercises, the potential of using sensors for data collection is explored, and the requirements are considered. The results show that the potential benefits are significant, especially for tracking patients, and understanding the interaction between the response actors. However, the sensors need to be quite advanced in order to capture the necessary data.
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Terje Gjøsæter, Jaziar Radianti, & Weiqin Chen. (2020). Towards Situational Disability-aware Universally Designed Information Support Systems for Enhanced Situational Awareness. 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. 1038–1047). Blacksburg, VA (USA): Virginia Tech.
Abstract: This paper takes on the challenge of designing situational awareness information systems that take into account not only the prevalence of so-called demons of situational awareness, but also situational disabilities that will typically occur in a disaster situation, both in the control room and in the field among the general public as well as first responders. It further outlines how a situational awareness information system process model can be adapted and used as a basis for designing situational awareness information support systems that address these issues with the help of Universal Design principles.
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Stephan Weijman, & Kenny Meesters. (2020). Shifting Control and Trust: Exploring Implications of Introducing Delegated Decision Support 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. 285–294). Blacksburg, VA (USA): Virginia Tech.
Abstract: Increased information access and more intelligent information systems enable more operators in an organization to autonomously make decisions. These delegated decision-making opportunities play an important role during critical events, as operators -such as emergency teams and responders- can work independently and rely less on a centralized decision-making structure. Moreover, the operators' perceived level of trust increases while also limiting the coordinators' perceived control. In this paper, we examine the influence of such systems on the shift in perceived control and empowerment for both operators and commanders. In our experiments, conducted at the Royal Netherlands Air Force, we found that the introduction of these systems indeed affects perceived control and empowerment, specifically as perceived by the coordinator. These factors will play an important role in the effective use of such systems and their transformative effect on an organization. Especially considering the ongoing technical and organizational developments in crisis information management.
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Stefan Schauer, Stefan Rass, Sandra König, Klaus Steinnocher, Thomas Schaberreiter, & Gerald Quirchmayr. (2020). Cross-Domain Risk Analysis to Strengthen City Resilience: the ODYSSEUS 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. 652–662). Blacksburg, VA (USA): Virginia Tech.
Abstract: In this article, we want to present the concept for a risk management approach to assess the condition of critical infrastructure networks within metropolitan areas, their interdependencies among each other and the potential cascading effects. In contrast to existing solutions, this concept aims at providing a holistic view on the variety of interconnected networks within a city and the complex dependencies among them. Therefore, stochastic models and simulations are integrated into risk management to improve the assessment of cascading effects and support decision makers in crisis situations. This holistic view will allow risk managers at the city administration as well as emergency organizations to understand the full consequences of an incident and plan mitigation actions accordingly. Additionally, the approach will help to further strengthen the resilience of the entire city as well as the individual critical infrastructures in crisis situations.
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Spyros Chrysanthopoulos, Theofanis Kapetanakis, Giannis Chaidemenos, Stelios Vernardos, Harris Georgiou, & Claudio Rossi. (2020). Emergency Response in Recent Urban/Suburban Disaster Events in Attica: Technology Gaps, Limitations and Lessons Learned. 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. 984–989). Blacksburg, VA (USA): Virginia Tech.
Abstract: Emergency response operations in large-scale urban/suburban disaster events is often addressed by the standard protocols and international guidelines for collapsed buildings, heavy debris, etc. However, a wide range of First Responder (FR) operations need to address various other contexts, work environments and hazards. In this paper, two real disaster events are explored as use cases for such urban/suburban FR operations, namely a flash flood and a wildfire, both in Attica, Greece (2017-2018). Based on our team's experience from these mobilizations and active participation in both these events as FR actor in the field, we present the challenges, the complexity of such multi-aspect disaster events, the limitations of emergency response, the technology gaps of the FR teams, as well as the lessons learned during these deployments. Finally, we make some notes on future prospects and possible advancements in tools and technologies that would greatly enhance the operational safety and readiness of the FR teams in such events.
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Sandrine Bubendorff, & Caroline Rizza. (2020). The Wikipedia Contribution to Social Resilience During Terrorist Attacks. 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. 790–801). Blacksburg, VA (USA): Virginia Tech.
Abstract: This paper aims at studying the role of Wikipedia in social resilience processes during terrorist attacks. It discusses how Wikipedia users' specific skills are mobilized in order to make sense of the event as it unfolds. We have conducted an ethnographic analysis of several Wikipedia's terrorist attacks pages as well as interviews with regular Wikipedia's contributors. We document how Wikipedia is used during crisis by readers and contributors. Doing so, we identify a specific pace of contributions which provides reliable information to readers. By discussing the conditions of their trustworthiness, we highlight how historical sources (i.e. traditional media and authorities) support this pace. Our analyses demonstrate that citizens are engaging very quickly in processes of resilience and should be, therefore, considered as relevant partners by authorities when engaging a response to the crisis.
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Samer Chehade, Nada Matta, Jean-Baptiste Pothin, & Remi Cogranne. (2020). Ontology-Based Approach for Designing User Interfaces: Application for Rescue Actors. 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. 54–65). Blacksburg, VA (USA): Virginia Tech.
Abstract: Nowadays, rescue actors still lack backing to exchange information effectively and ensure a common operational picture. Several studies report a low adoption of communication systems in rescue operations as well as a negative position of actors to such systems. The real needs of stakeholders, simply put, are not satisfied by the offered systems. Observing this circumstance through a user-centred design focal point, we notice that such issues ordinarily originate from inadequate design techniques. For this reason, we aim to implement Rescue MODES, a communication system oriented to support awareness amongst French actors in rescue operations based on their needs. In this paper, we propose an approach and introduce a platform that allows final users to design system interfaces in a customised way. This approach is based on an application ontology and an interaction model.
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Ryan K. Williams, Nicole Abaid, James McClure, Nathan Lau, Larkin Heintzman, Amanda Hashimoto, et al. (2020). Collaborative Multi-Robot Multi-Human Teams in Search and Rescue. 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. 973–983). Blacksburg, VA (USA): Virginia Tech.
Abstract: Robots such as unmanned aerial vehicles (UAVs) deployed for search and rescue (SAR) can explore areas where human searchers cannot easily go and gather information on scales that can transform SAR strategy. Multi-UAV teams therefore have the potential to transform SAR by augmenting the capabilities of human teams and providing information that would otherwise be inaccessible. Our research aims to develop new theory and technologies for field deploying autonomous UAVs and managing multi-UAV teams working in concert with multi-human teams for SAR. Specifically, in this paper we summarize our work in progress towards these goals, including: (1) a multi-UAV search path planner that adapts to human behavior; (2) an in-field distributed computing prototype that supports multi-UAV computation and communication; (3) behavioral modeling that yields spatially localized predictions of lost person location; and (4) an interface between human searchers and UAVs that facilitates human-UAV interaction over a wide range of autonomy.
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Rob Grace. (2020). Hyperlocal Toponym Usage in Storm-Related Social Media. 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. 849–859). Blacksburg, VA (USA): Virginia Tech.
Abstract: Crisis responders need to locate events reported in social media messages that typically lack geographic metadata such as geotags. Toponyms, places names referenced in messages, provide another source of geographic information, however, the availability and granularity of toponyms in crisis social media remain poorly understood. This study examines toponym usage and granularity across six categories of crisis-related information posted on Twitter during a severe storm. Findings show users often include geographic information in messages describing local and remote storm events but do so rarely when discussing other topics, more often use toponyms than geotags when describing local events, and tend to include fine-grained toponyms in reports of infrastructure damage and service disruption and course-grained toponyms in other kinds of storm-related messages. These findings present requirements for hyperlocal geoparsing techniques and suggest that social media monitoring presents more immediate affordances for course-grained damage assessment than fine-grained situational awareness during a crisis.
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Richard McCreadie, Cody Buntain, & Ian Soboroff. (2020). Incident Streams 2019: Actionable Insights and How to Find Them. 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. 744–760). Blacksburg, VA (USA): Virginia Tech.
Abstract: The ubiquity of mobile internet-enabled devices combined with wide-spread social media use during emergencies is posing new challenges for response personnel. In particular, service operators are now expected to monitor these online channels to extract actionable insights and answer questions from the public. A lack of adequate tools makes this monitoring impractical at the scale of many emergencies. The TREC Incident Streams (TREC-IS) track drives research into solving this technology gap by bringing together academia and industry to develop techniques for extracting actionable insights from social media streams during emergencies. This paper covers the second year of TREC-IS, hosted in 2019 with two editions, 2019-A and 2019-B, contributing 12 new events and approximately 20,000 new tweets across 25 information categories, with 15 research groups participating across the world. This paper provides an overview of these new editions, actionable insights from data labelling, and the automated techniques employed by participant systems that appear most effective.
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Rahul Pandey, Brenda Bannan, & Hemant Purohit. (2020). CitizenHelper-training: AI-infused System for Multimodal Analytics to assist Training Exercise Debriefs at Emergency Services. 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. 42–53). Blacksburg, VA (USA): Virginia Tech.
Abstract: The adoption of Artificial Intelligence (AI) technologies across various real-world applications for human performance augmentation demonstrates an unprecedented opportunity for emergency management. However, the current exploration of AI technologies such as computer vision and natural language processing is highly focused on emergency response and less investigated for the preparedness and mitigation phases. The training exercises for emergency services are critical to preparing responders to perform effectively in the real-world, providing a venue to leverage AI technologies. In this paper, we demonstrate an application of AI to address the challenges in augmenting the performance of instructors or trainers in such training exercises in real-time, with the explicit aim of reducing cognitive overload in extracting relevant knowledge from the voluminous multimodal data including video recordings and IoT sensor streams. We present an AI-infused system design for multimodal stream analytics and lessons from its use during a regional training exercise for active violence events.
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Pouyan Fotouhi Tehrani, Niklas von Kalckreuth, & Selma Lamprecht. (2020). Toward an Integrative Model of Trust for Digital Emergency Communication. 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. 1012–1021). Blacksburg, VA (USA): Virginia Tech.
Abstract: Digital technologies have become an integral enabler of communication during various phases of emergency management (EM). A crucial prerequisite of effective communication between authorities and the public during EM is the establishment of adequate mutual trust. Trust, however, is an elusive concept which is not easily translatable into technical settings. In this paper we propose an integrative model of trust in digital communication and show how such model can be advantageous in assessing and improving trust relations in context of EM. Our interdisciplinary model, which is based on findings from psychology, sociology and computer sciences provides an abstraction which not only seizes both subjective and objective as well as personal and non-personal, \eg institutional or cultural, aspects of trust but at the same time is concrete enough to be applicable to real-life scenarios.
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Per-Anders Oskarsson, Magdalena Granåsen, Niklas Hallberg, & Mari Olsén. (2020). Modeling of Crisis Management Systems: Results of a Systematic Literature Review. 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. 435–447). Blacksburg, VA (USA): Virginia Tech.
Abstract: Models are important means to represent, explore, evaluate, and develop systems, such as interorganizational crisis management (ICM) systems. The objective was to explore how ICM systems are represented in the scientific literature, i.e., how ICM systems are modelled. The study was carried out as a systematic literature review. The results are presented as (1) organizational descriptions or models of ICM systems, (2) functional components of ICM systems, (3) analytical approaches used to model ICM systems, and (4) changes of ICM systems. The results revealed that ICM systems are described in various ways, and that descriptions of models are rather based on entities developed by the authors of the publications than on a common framework for describing ICM systems. The identified information on models, functional components, analytical approaches, and changes of the ICM systems provide important input to future work, e.g. comparing different models to determine their strengths and weaknesses.
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Pengfei Zhou, Tao Chen, Guofeng Su, Bingxu Hou, & Lida Huang. (2020). Research on the Forecasting and Risk Analysis Method of Snowmelt Flood. 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. 545–557). Blacksburg, VA (USA): Virginia Tech.
Abstract: Risk analysis of snowmelt flood is an urgent demand in cold highland areas. This paper focuses on the method for the rapid and reliable forecast of daily snowmelt, snow water runoff, and snowmelt flood risk. A neural network algorithm is used to calculate snow density distribution, snow depth and snow-water equivalent with the brightness temperature data. Then, daily snowmelt is predicted using the degree-day factor method with the temperature distribution. On this basis, we use the steepest descent method and Manning formula with hydrographic information to simulate snow water runoff. We also propose a method to predict the snowmelt flood risk with the geographic feature and historical flood data. The evaluated risk is compared with monitored data in the Xinjiang Autonomous Region of China, which shows good consistency. At last, we develop a risk analysis system to generate the snowmelt flood risk map and provide risk analysis service.
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Paulina Potemski, Nada Matta, & Patrick Laclémence. (2020). Modelling Women's Living Conditions' in Violence using KM techniques. 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. 27–34). Blacksburg, VA (USA): Virginia Tech.
Abstract: According to the United Nations Secretary General, gender equality has advanced in recent decades we are leaving in unprecedented global efforts to advance on women' empowerment. For example, girls' access to education has improved, the rate of child marriage declined and progress was made in the area of sexual and reproductive health and reproductive rights, including fewer maternal deaths. Nevertheless, gender equality remains a persistent challenge for countries worldwide and the lack of such equality is a major obstacle to sustainable development (Golombok et al, 1994, UNSG report, 2017). There are various inequity factors women confront. Women are the population that suffers most from different forms of discrimination. All of them root women's inferiority, women's dependence and as a matter of consequence, create a vicious circle of a domination system. Domination systems of men over women are all the more pernicious and harsher when combined with extreme poverty, remote living areas and conflicts. We discuss in this paper the fact that women are the population which underlive most difficult living conditions especially when violence and tradition are combined. Modelling life conditions put on the main factors of this violence and its consequences.
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Patricia Quiroz-Palma, Ma Carmen Penadés, & Ana-Gabriela Núñez. (2020). Resilience Learning for Emergency Plan Management in Organizations. 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. 558–567). Blacksburg, VA (USA): Virginia Tech.
Abstract: Many governments, organizations, practitioners and researchers involved in collaboration on resilience in emergency management are agreed that this is a key aspect. The QuEP+R framework aims to improve resilience in an organization's emergency plan management, in which the stakeholders must be adequately prepared and trained for their responsibilities in the emergency plan, providing techniques that propose the improvement of the emergency plan besides resilience. However, for these techniques to be effective, organizations need the theoretical resilience proposed in QuE+R to be implemented. The CiET framework was designed for this purpose and has learning objectives and training contents related to QuEP+R techniques to train stakeholders. The CiET capability plan contents have been classified by resilience dimensions towards the optimization of resilience in emergency plan management. The integration is supported by I+R-Tool, which generates the capability plans automatically from the results of the QuEP+R assessment, which outcomes in a stakeholder's effective training, contributing to the optimization and improvement of the resilience, therefore, in improving the quality of emergency plans. Hence, the aim remains to search for the continuous improvement of the emergency plan management within organizations.
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