Louis Ngamassi, Abish Malik, Jiawei Zhang, & David Edbert. (2017). Social Media Visual Analytic Toolkits for Disaster Management: A Review of the Literature. 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. 785–797). Albi, France: Iscram.
Abstract: The past decade has seen a significant increase in the use of social media for disaster management. This is due especially to the widespread usage of mobile devices and also to the different data types and data formats that social media supports. In recent years, research in the area of social media visual analytics has also gained interest in the scientific community. Research in this area however, lacks a comprehensive overview on social media visual analytics for disaster management. Hence, this paper presents a synthesis of extant research on social media visual analytic and visualization toolkits for disaster management. We survey available literature on these tools with the goal to outline the major characteristics and features, and to examine the extent to which they cover the full cycle of disaster management. Our main purpose is to provide a foundation based on the current literature that can help to shape future research directions to enhance social media visual analytic tools for full cycle disaster management.
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Louis Ngamassi, Thiagarajan Ramakrishnan, & Shahedur Rahman. (2016). Examining the Role of Social Media in Disaster Management from an Attribution Theory Perspective. 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: This paper is related to the use of social media for disaster management by humanitarian organizations. The past decade has seen a significant increase in the use of social media to manage humanitarian disasters. It seems, however, that it has still not been used to its full potential. In this paper, we examine the use of social media in disaster management through the lens of Attribution Theory. Attribution Theory posits that people look for the causes of events, especially unexpected and negative events. The two major characteristics of disasters are that they are unexpected and have negative outcomes/impacts. Thus, Attribution Theory may be a good fit for explaining social media adoption patterns by emergency managers. We propose a model, based on Attribution Theory, which is designed to understand the use of social media during the mitigation and preparedness phases of disaster management. We also discuss the theoretical contributions and some practical implications. This study is still in its nascent stage and is research in progress.
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Louis Ngamassi, Thiagarajan Ramakrishnan, & Shahedur Rahman. (2020). Investigating the Use of Social Media by Underserved Communities for 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. 490–496). Blacksburg, VA (USA): Virginia Tech.
Abstract: Social media is emerging as a communication tool for successfully managing disasters. However, studies have shown that not all individuals are equally predisposed towards effectively using social media for disaster management. There still exists a big digital divide when it comes to using social media for disaster management. Drawing on situational theory of problem solving, we develop a conceptual model that examines the motivating factors for the underserved communities to use social media for disaster management. We further develop and cross-validate a questionnaire instrument to acilitate empirical research. We thus offer an empirical context for motivating individuals from underserved communities to use social media effectively during disasters.
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Alessio Malizia, Francisco Astorga-Paliza, Teresa Onorati, Paloma Díaz, & Ignacio Aedo. (2008). Emergency alerts for all: An ontology based approach to improve accessibility in emergency alerting systems. In B. V. de W. F. Fiedrich (Ed.), Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management (pp. 197–207). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: When a disaster occurs it is critical that emergency response information systems share a common ontology to support their disaster management alerting functions and notifications. Notifications are critical when an emergency scenario is going to happen (e.g. a typhoon approaching) so it is crucial, for emergency systems, to be able to transmit them to all kinds of recipients. An ontology was developed by investigating different sources: accessibility guidelines, emergency response systems, communication devices and technologies, taking into account the different abilities of people to react to different alarms (e.g. mobile phone vibration as an alarm for deaf people). We think that the proposed ontology addresses the information needs for sharing and integrating emergency notification messages and contents over different emergency response information systems and to be accessible under different conditions and for different kind of users.
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Marc Schönefeld, & Malte Schönefeld. (2020). IT-Security Awareness of Emergency Alert Apps. 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. 396–405). Blacksburg, VA (USA): Virginia Tech.
Abstract: The article presents first research-in-progress results of an initial assessment of the IT-security awareness of five exemplary German-language emergency-alert apps. Emergency-alert mobile applications became part of many modular-oriented warning systems around the globe. Warning and intended population behavior relies on trust upon the integrity of any warning institution, be it governmental or private. IT-security is crucial in order not to undermine trust. Emergency apps do not fit into the typical entertainment purpose of mobile applications, and we show that their primarily focus on keeping the user safe from harm can cause a conflict of interest about distribution of scarce technical resources on a mobile device, which may again endanger IT-Security. We therefore promote a better integration and standardization of disaster management functionality on the operating system layer.
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Marcello Cinque, Christian Esposito, Mario Fiorentino, & Francisco Jose Perez Carrasco. (2015). A collaboration platform for data sharing among heterogeneous relief organizations for disaster management. 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: Recently, we are witnessing the progressive increase in the occurrence of large-scale disasters, characterized by an overwhelming scale and number of causalities. After 72 hours from the disaster occurrence, the damaged area is interested by assessment, reconstruction and recovery actions from several heterogeneous organizations, which need to collaborate and being orchestrated by a centralized authority. This situation requires an effective data sharing by means of a proper middleware platform able to let such organizations to interoperate despite of their differences. Although international organizations have defined collaboration frameworks at the higher level, there is no ICT supporting platform at operational level able to realize the data sharing demanded by such collaborative frameworks. This work proposes a layered architecture and a preliminary implementation of such a middleware for messaging, data and knowledge management. We also illustrate a demonstration of the usability of such an implementation, so as to show the achievable interoperability.
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Kenny Meesters, & Bartel A. Van De Walle. (2013). Disaster in my backyard: A serious game introduction to disaster information management. 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. 145–150). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: Disaster exercises are intended to improve disaster responses effectiveness. Exercises exist in a wide variety, ranging from table-top scenarios to full-scale disaster simulations, offering participants different learning experiences. However these exercises can be overwhelming to newcomers, especially when involving large scale simulations, reducing the effectiveness of the learning experience. In order to make the learning experiences more effective to newcomers, researchers or professionals, a new exercise is proposed. This exercise, designed as a serious game, provides a new way to introduce people to the field of disaster management in general and information management in particular. The first version of the game was played during the 2012 ISCRAM summer school where it yielded positive reactions from both novice participants and experienced professionals.
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Ulrich Meissen, & Frank Fuchs-Kittowski. (2014). Towards a reference architecture of crowdsourcing integration in early warning systems. 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. 334–338). University Park, PA: The Pennsylvania State University.
Abstract: Crowdsourcing has the potential to become a crucial information source in disaster management. In order to become effective as an integrated part of disaster management systems it is important to set the general architectural foundations for such integrations beyond prototypical experiments. This paper discusses general architectural principles of the application of crowdsourcing in Early Warning Systems (EWS). An integrated architecture is proposed to use classical sensor data and crowdsourcing in an EWS solution. Therefore, typical components of crowdsourcing applications are identified and mapped to monitoring subsystems of EWS's. Three main structural variants of applying crowdsourcing in early warning systems along the example of a prototypical extension of two existing large-scale hydro-meteorological warning systems are presented.
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Melanie Eckle, & João Porto de Albuquerque. (2015). Quality Assessment of Remote Mapping in OpenStreetMap for Disaster Management Purposes. 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: Over the last couple of years Volunteered Geographic Information (VGI) and particularly OpenStreetMap (OSM) have emerged as an important additional source of information in disaster management. The so-called OSM Crisis Maps are primarily developed by OSM contributors who work remotely. While local OSM contributors know their area of interest and rely upon local knowledge, often the sole basis for the remote mapping is satellite imagery. This fact may raise doubts about the quality of the Crisis Maps. This study introduces an experimental approach to assess the data quality that remote mappers produce. In an experimental setting, data sets produced by a group of remote mappers are evaluated by comparing them to data sets created by a selected expert mapper with local knowledge. The presented approach proved to be useful for assessing data quality of remote mapping and can be used to support decisions about the suitability of crowdsourced geographic data.
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Michael Auer, Melanie Eckle, Sascha Fendrich, Luisa Griesbaum, Fabian Kowatsch, Sabrina Marx, et al. (2018). Towards Using the Potential of OpenStreetMap History for Disaster Activation Monitoring. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 317–325). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: “Over the last couple of years, the growing OpenStreetMap (OSM) data base repeatedly proved its potential for various use cases, including disaster management. Disaster mapping activations show increasing contributions, but oftentimes raise questions related to the quality of the provided \emph{Volunteered Geographic Information} (VGI). In order to better monitor and understand OSM mapping and data quality, we developed a software platform that applies big data technology to OSM full history data. OSM full history data monitoring allows detailed analyses of the OSM data evolution and the detection of remarkable patterns over time. This paper illustrates the specific potential of the platform for disaster activations by means of two case studies. Initial results demonstrate that our flexible and scalable platform structure enables fast and easy information extraction and supports mapping processes and data quality assurance.”
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Michael Aupetit, & Muhammad Imran. (2017). Interactive Monitoring of Critical Situational Information on Social Media. 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. 673–683). Albi, France: Iscram.
Abstract: According to many existing studies, the data available on social media platforms such as Twitter at the onset of a crisis situation could be useful for disaster response and management. However, making sense of this huge data coming at high-rate is still a challenging task for crisis managers. In this work, we present an interactive social media monitoring tool that uses a supervised classification engine and natural language processing techniques to provide a detailed view of an on-going situation. The tool allows users to apply various filtering options using interactive timelines, critical entities, and other logical operators to get quick access to situational information. The evaluation of the tool conducted with crisis managers shows its significance for situational awareness and other crisis management related tasks.
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Stella Moehrle. (2012). Generic self-learning decision support system for large-scale disasters. 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: Large-scale disasters, particularly failures of critical infrastructures, are exceptional situations which cannot be solved with standard countermeasures. The crises are complex and the decision makers face acute time pressure to respond to the disaster. IT based decision support systems provide potential solutions and assist the decision making process. Many decision support systems in emergency response and management concentrate on one kind of disaster. Moreover, complex structures are modeled and recommendations are made rule-based. This work in progress paper describes the first steps towards the development of a generic and self-learning decision support system. The methodology used is case-based reasoning. The paper concludes with a sample emergency decision process. © 2012 ISCRAM.
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Stella Moehrle. (2013). Modeling of countermeasures for large-scale disasters using high-level petri nets. 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. 284–289). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: In order to support decision-making in large-scale disasters, IT-based decision support systems provide appropriate countermeasures to respond to the event. For the implementation of measures, logical and temporal dependencies have to be considered. Furthermore, factors influencing the choice of measures should be taken into account. This paper presents a generic approach to modeling sequences of countermeasures using Highlevel Petri Nets including information about the influencing factors and endangered objects. Moreover, an approach to combining several nets is proposed, which establish new sequences for recommendation. The research is part of the development of a generic decision support system for large-scale disasters. Consequently, the focus is on modeling in a generic manner and on automatic processing.
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Stella Moehrle. (2014). On the assessment of disaster management strategies. 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. 215–219). University Park, PA: The Pennsylvania State University.
Abstract: Decision support systems can recommend strategies for disaster management, which can be further discussed by decision-makers. To provide rationales for the recommendations, the strategies need to be assessed according to relevant criteria. If several strategies are available, the criteria can be used for ranking the strategies. This paper addresses the issue concerning the choice of suitable criteria from several perspectives. The assessment integrates concepts on robustness, experience with regard to the implementation of a strategy, quantifiable ratios which can be deduced from simulations, and system-specific parameters. Objectives are to facilitate transparency with respect to the assessments, to provide a basis for discussions concerning the strategies, and to preserve adaptability and flexibility to account for the variability of disasters and users' preferences. The assessment should be used for ranking solutions gained from a case-based reasoning system and to reveal contributions of criteria values to the overall assessment.
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Monika Magnusson, Lars Nyberg, & Malin Wik. (2018). Information Systems for Disaster Management Training – Establishing User Needs with a Design Science Research Approach. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 841–850). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: Societal threats such as global warming and terror attacks make crisis preparedness and crisis training a major priority in governments worldwide. Unfortunately, training is limited, partly due to complex and resource-demanding planning of traditional exercises. Several crisis training software have been developed as a complement. However, reports in research on their usage are rare, which indicates that the diffusion is limited. A potential explanation is that the systems fail to meet important needs in the organizations and/or sound information systems (IS) design principles. This paper describes the first phase of a design science research (DSR) project aiming at developing information systems for disaster management (ISDM) training, and accompanying training methods in local and regional governments. The purpose of this paper is to investigate perceived problems in current crisis training and identify opportunities for ISDM training in the application domain. Another purpose is to outline expected artifacts in the project.
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Thomas Münzberg, Tim Müller, Stella Möhrle, Tina Comes, & Frank Schultmann. (2013). An integrated multi-criteria approach on vulnerability analysis in the context of load reduction. 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. 251–260). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: Load reduction is an emergency measure to stabilize an electrical grid by decoupling some supply areas to balance the demand and supply of electricity in power grids. In the decoupled areas, power outages may cause important consequences, which may propagate further via the network of interdependent infrastructures. Therefore, support is needed to choose the regions to be decoupled. This paper describes an approach to analyze the risk triggered by load reduction that can be used for disaster management and load reduction scheme optimization. The core of our work is the vulnerability assessment that takes into account the consequences of load reduction on economy and society. The approach facilitates participatory decision support by making the vulnerability of regions especially in urban transparent.
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Thomas Münzberg, Ulrich Berbner, Tina Comes, Hanno Friedrich, Wendelin Groß, Hans-Christian Pfohl, et al. (2013). Decision support for critical infrastructure disruptions: An integrated approach to secure food supply. 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. 312–316). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: Supplies of food and water are essential in disaster management, particularly in the very early chaotic phases when demand and available resources are highly uncertain, information systems are disrupted, and communication between communities, food suppliers, retail and emergency authorities is difficult. As many actors and organisations are involved in ever more complex food supply chains, cooperation and collaboration are vital for efficient and effective disaster management. To support decision-makers facing these problems, this paper introduces a scenario-based approach that integrates simulation of disruptions in food supply chains, and qualitative expert assessment to develop consistent scenarios that show the consequences of different strategies. To choose the best individual measures for all relevant actors and to compare it with the best overall strategy approaches from multi-criteria decision analysis are used.
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Ahmed Nagy, Lusine Mkrtchyan, & Klaas Van Der Meer. (2013). A CBRN detection framework using fuzzy logic. 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. 266–271). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: Identifying a chemical, biological, radiological, and nuclear incident (CBRN) is a challenge. Evidence and health symptoms resulting from CBRN malevolent incident overlap with other normal non malevolent human activities. However, proper fusion of symptoms and evidence can aid in drawing conclusions with a certain degree of credibility about the existence of an incident. There are two types of incidents directly observable, overt, or indirectly observable, covert, which can be detected from the symptoms and consequences. This paper describes a framework for identifying a CBRN incident from available evidence using a fuzzy belief degree distributed approach. We present two approaches for evidence fusion and aggregation; the first, two level cumulative belief degree (CBD) while the second is ordered weighted aggregation of belief degrees (OWA). The evaluation approach undertaken shows the potential value of the two techniques.
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Samuel Otim. (2006). A case-based knowledge management system for disaster management: Fundamental concepts. In M. T. B. Van de Walle (Ed.), Proceedings of ISCRAM 2006 – 3rd International Conference on Information Systems for Crisis Response and Management (pp. 598–604). Newark, NJ: Royal Flemish Academy of Belgium.
Abstract: Computer-based knowledge management systems are vital for disaster detection, response planning, and management. These systems aid in early warning, and provide decision support for disaster response and recovery management. Managing past knowledge for reuse can expedite the process of disaster response and recovery management. While early warning systems predict some disasters with remarkable accuracy, there is a paucity of knowledge management systems for disaster response and management. This paper outlines a case-based reasoning (CBR) knowledge management system that in effect, is a model of human reasoning since it is based upon the idea that people frequently rely on previous problem-solving experiences when solving new problems. A CBR knowledge management system results in efficient and effective disaster response and management.
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Nicholas Palmer, Roelof Kemp, Thilo Kielmann, & Henri Bal. (2012). RAVEN: Using smartphones for collaborative disaster data collection. 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: In this paper we describe our work in progress on RAVEN, a framework, which makes it possible to build applications for collaborative editing of structured data on Android. RAVEN offers developers compile time tools, which use only the schema to generate all database handling components, edit and list user interfaces, as well as those needed for data synchronization, significantly reducing development effort. In addition, RAVEN also offers the ability to do the same work, entirely at runtime, using only a smartphone. With RAVEN it is possible to construct data oriented applications on phone at any time, including during a disaster. Users can share their applications simply by sharing the database and corresponding schema. Thus, RAVEN enables completely decentralized application creation, sharing, and data distribution, avoiding issues of connectivity to centralized resources. In this paper we show that with RAVEN it is possible to construct a new application at runtime and compare the results with an equivalent custom-built application. © 2012 ISCRAM.
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Christian Paulus, Stefan Möllmann, & Hagen Engelmann. (2010). Approach for an integrated interoperable system architecture for disaster management systems. 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 the field of information systems for disaster management there is a large variety of data formats, specifications and standards. Most of these standards only cover a specific part of this area, for example formats for geospatial data or message exchange. This diversity of isolated solutions, however, prevents those systems from interacting and exchanging data. To improve the interoperability in this sector there is a strong need for an integrated interoperable system architecture that is suitable for stand-alone systems as well as for the communication in a distributed heterogeneous system environment. This paper shows an approach for such a system architecture. It presents the Disaster Management Markup Language (DMML), which provides an architecture of data structures, services and service interfaces for crisis response systems. Furthermore, the Disaster Management Interoperability Framework (DMIF) is introduced, which supplies a software-engineering layout for DMML. Finally, the implementation of the DMMapML module is presented, which handles data involved in the situation report. The basic structure of this implementation is described and its potential contribution to the interoperability of crisis response systems.
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Rahman, S., Ramakrishnan, T., & Ngamassi, L. (2023). Social Media Use for Disaster Management by Underserved Communities: A Uses and Gratification Theory Perspective. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (p. 1074). Omaha, USA: University of Nebraska at Omaha.
Abstract: Social media has emerged as a useful disaster management tool. However, studies indicate that not all individuals are equally inclined towards using social media for managing disasters. Underserved communities have not been able to reap the benefits of social media for disaster management to its full potential. We draw on the Uses and Gratification Theory and the literature on disaster vulnerability of underserved communities to develop a conceptual model. In our poster, we make five propositions in order to examine the motivating factors for the underserved communities to use social media for disaster management.
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Rahul Pandey, Gaurav Bahl, & Hemant Purohit. (2019). EMAssistant: A Learning Analytics System for Social and Web Data Filtering to Assist Trainees and Volunteers of Emergency Services. 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: An increasing number of Machine Learning based systems are being designed to filter and visualize the relevant
information from social media and web streams for disaster management. Given the dynamic disaster events, the
notion of relevant information evolves, and thus, the active learning techniques are often considered to keep
updating the predictive models for the relevant information filtering. However, the active relevant feedback
provided by the human annotators to update the models are not validated. As a result, they can introduce
unconscious biases in the learning process of humans and can result in an inaccurate or inefficient predictive
system. Therefore, this paper describes the design and implementation of an open-source technology-based
learning analytics system ? EMAssistant ? for the emergency volunteers or practitioners – referred as the trainee, to
enhance their experiential learning cycle with the cause-effect reasoning on providing relevant feedback to the
machine learning model. This continuous integration between the cause (providing feedback) and the effect
(observing predictions from the updated model) in a visual form will likely to improve the understanding of the
trainees to provide more accurate feedback. We propose to present the system design as well as provide
hands-on exercises for the conference session.
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Reem Abbas, & Tony Norris. (2018). Inter-Agency Communication and Information Exchange in Disaster Healthcare. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 886–892). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: In a disaster, the main agencies of healthcare and relief are usually health and disaster management organisations. Although these two disciplines share the same vision of care provision to disaster victims, experience shows that poor communication between them can negatively impact the collaboration needed to ensure the quality and coordinated delivery of effective healthcare. This paper presents the current findings of an on-going investigation to determine and reduce the barriers to smooth and effective communication and information exchange.
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Robert Power, Bella Robinson, David Alexander, & Mahesh Prakash. (2018). Predicting Demand for Government Services during Disaster Events. In Kristin Stock, & Deborah Bunker (Eds.), Proceedings of ISCRAM Asia Pacific 2018: Innovating for Resilience – 1st International Conference on Information Systems for Crisis Response and Management Asia Pacific. (pp. 89–96). Albany, Auckland, New Zealand: Massey Univeristy.
Abstract: Smart Service Queensland (SSQ) is the 'front door' to the Queensland State Government in Australia, providing services and information for citizens and businesses. Services are delivered through online channels, call centres and face-to-face service centres. Rostering to adequately staff the call centres during business as usual demand is well supported using existing workforce planning tools and content management systems alongside real-time telephonic monitoring. However, during times of large scale emergency events, such as floods and tropical cyclones, effective workforce planning heavily relies upon experienced SSQ personnel constantly monitoring and updating call centre staffing levels leading up to and during the disaster event to ensure customer demands are met. Achieving the right balance of call centre servicing without over provisioning is a challenging task. We present a prototype analytics tool that supports the SSQ Forecast Analyst responsible for workforce planning during disaster events and provides initial results of modelling caller behavior during two recent tropical cyclones. The tool provides a single point of reference to a wide collection of relevant datasets, including population demographics and details of the natural and built environment, data feeds describing the emergency event under investigation, relevant social media posts and call centre operations metrics. The tool is an early proof of concept demonstrator highlighting the utility of data integration, web mapping, real-time event monitoring, and predictive modelling.
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