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Anne Marie Barthe, Sébastien Truptil, & Frédérick Bénaben. (2014). Agility of crisis response: Gathering and analyzing data through an event-driven platform. 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. 250–254). University Park, PA: The Pennsylvania State University.
Abstract: The goal of this article is to introduce a platform (called Agility Service) that gathers and analyses data coming from both crisis response and crisis field by using the principles of Complex Event Processing. As a crisis situation is an unstable phenomenon (by nature or by effect of the applied response), the crisis response may be irrelevant after a while: lack of resources, arrival of a new stakeholder, unreached objectives, over-crisis, etc. Gathering data, analyze and aggregate it to deduce relevant information concerning the current crisis situation, and making this information available to the crisis cell to support decision making: these are the purposes of the described platform. A use case based on the Fukushima's nuclear accident is developed to illustrate the use of the developed prototype.
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Aaron Burgman, Nikhil Kalghatgi, Erika Darling, Chris M. Newbern, Kristine Recktenwald, Shawn Chin, et al. (2006). Emergency data analysis via semantic lensing. In M. T. B. Van de Walle (Ed.), Proceedings of ISCRAM 2006 – 3rd International Conference on Information Systems for Crisis Response and Management (pp. 334–338). Newark, NJ: Royal Flemish Academy of Belgium.
Abstract: Emergency situations often play out over extended geographic regions and can present response personnel with numerous types of data at various level of detail. Such data may be displayed in mapping software tools that organize the data into layers. Sufficiently complex scenarios can result in dense, occluded, and cluttered map displays. We investigated a localized, detail-on-demand filtering strategy called semantic lensing that in certain situations provides a more efficient and desirable approach than filtering global layers for mitigating clutter and occlusion. An initial formal user study with these semantic lenses has shown their value in aiding decision makers during tasks that might occur during detection of and response to emergency situations. Completion times are significantly faster when using lenses, and workloads are significantly lower. Future work will evaluate additional features and task-specific applicability, and may support the distribution of such a lens tool to emergency preparedness and response personnel.
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Abbas Ganji, Tom Wilson, Sonia Saveli, Dharma Dailey, & Mark Haselkorn. (2019). Cause and Effect: A Qualitative Analysis of Obstacles to Information Sharing During a Regional Disaster Exercise. 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: After large-scale disasters, diverse partner agencies rely heavily on an information-sharing environment that supports collaborative work. In the U.S., this occurs under the Incident Command System (ICS), a structured organizational framework for coordinated action. We explore obstacles to information sharing and coordinationobserved at a county-level Emergency Operations Center (EOC) operating under ICS during the response phase of a large-scale regional disaster exercise. Textual observations collected in situ are analyzed for both the effect/manifestation and cause/source of barriers to information sharing. Two-thirds of barriers that manifest as computational issues are not caused by technology breakdowns, and a third caused by unclear processes manifest as computational issues. Overall, obstacles to collaborative work that appear to be related to computational issues are generally attributable to non-technical causes. This indicates that resources directed at improving collaborative management of disasters by enhancing technological capabilities are likely to be misdirected.
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Adam Widera, Hanns-Alexander Dietrich, Bernd Hellingrath, & Jörg Becker. (2013). Understanding humanitarian supply chains – Developing an integrated process analysis toolkit. 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. 210–219). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: In this paper we present the development of an integrated process analysis toolkit for humanitarian logistics. The toolkit integrates a conceptual and a technological component. Our approach follows a case study-based modeling and design approach. The developed concept was evaluated in two humanitarian organizations. Based on these results we extended and integrated the tool-supported process analysis approach, which is ready to use for the structural and quantitative analysis of humanitarian logistics processes. The toolkit can be applied in humanitarian organizations as a decision support tool for designing, planning and executing their logistics processes. Thus, the application affects the preparedness of humanitarian organizations as well as their response performance. The process analysis toolkit is embedded in an overall research agenda with the objective to provide humanitarian organizations with the capabilities to identify, monitor, and improve their logistics processes respecting the organization specific objectives.
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Adriaan ter Mors, Jeroen M. Valk, & Cees Witteveen. (2005). An event-based task framework for disaster planning and decision support. In B. C. B. Van de Walle (Ed.), Proceedings of ISCRAM 2005 – 2nd International Conference on Information Systems for Crisis Response and Management (pp. 151–153). Brussels: Royal Flemish Academy of Belgium.
Abstract: Because of the apparent ineffectiveness of current disaster plans, we focus our research on modeling emergency response activities. If we can capture the crucial concepts of emergency response in a mathematical framework and apply this framework to construct disaster plans, then we pave the way for the development of automated decisions support systems for emergency response.
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Ahmed Nagy, & Jeannie Stamberger. (2012). Crowd sentiment detection during disasters and crises. 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: Microblogs are an opportunity for scavenging critical information such as sentiments. This information can be used to detect rapidly the sentiment of the crowd towards crises or disasters. It can be used as an effective tool to inform humanitarian efforts, and improve the ways in which informative messages are crafted for the crowd regarding an event. Unique characteristics of microblogs (lack of context, use of jargon etc) in Tweets expressed by a message-sharing social network during a disaster response require special handling to identify sentiment. We present a systematic evaluation of approaches to accurately and precisely identify sentiment in these Tweets. This paper describes sentiment detection expressed in 3698 Tweets, collected during the September 2010, San Bruno, California gas explosion and resulting fires. The data collected was manually coded to benchmark our techniques. We start by using a library of words with annotated sentiment, SentiWordNet 3.0, to detect the basic sentiment of each Tweet. We complemented that technique by adding a comprehensive list of emoticons, a sentiment based dictionary and a list of out-of-vocabulary words that are popular in brief, online text communications such as lol, wow, etc. Our technique performed 27% better than Bayesian Networks alone, and the combination of Bayesian networks with annotated lists provided marginal improvements in sentiment detection than various combinations of lists. © 2012 ISCRAM.
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Ahmed S. Khalaf, Poom Pianpak, Sultan A. Alharthi, Zahra NaminiMianji, Ruth Torres, Son Tran, et al. (2018). An Architecture for Simulating Drones in Mixed Reality Games to Explore Future Search and Rescue Scenarios. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 971–982). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: The proliferation of unmanned aerial systems (i.e., drones) can provide great value to the future of search and rescue. However, with the increase adoption of such systems, issues around hybrid human-drone team coordination and planning will arise. To address these early challenges, we provide insights into the development of testbeds in the form of mixed reality games with simulated drones. This research presents an architecture to address challenges and opportunities in using drones for search and rescue. On this architecture, we develop a mixed reality game in which human players engage with the physical world and with gameplay that is purely virtual. We expect the architecture to be useful to a range of researchers an practitioners, forming the basis for investigating and training within this unique, new domain.
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Aibek Musaev, Kimberly Stowers, & Jonghun Kam. (2018). Harnessing Data to Create an Effective Drought Management System. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 544–552). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: Drought is a complex climate phenomenon with slow emergence and quick vanish, which makes it hard for stakeholders to respond to drought timely. To reduce the vulnerability of our society to future drought, a better understanding of how society responds to drought is critical. Here, we propose a pilot study about social response to a recent California drought through social media. In this study, we identify the most important users using an extension of PageRank algorithm. We investigate the key drivers of the public activity in February, 2014 during the California drought. We also create a word cloud visualization from the most retweeted tweets. Lastly, we specify the information sources from those tweets. The findings of this study inform us that big data can help us to improve the current drought response plans through fundamental understanding of social response to drought, which is applicable to other natural hazards.
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Aladdin Shamoug, Radmila Juric, & Shamimabi Paurobally. (2012). Ontological reasoning as a tool for humanitarian decision making. 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: We propose an OWL/SWRL enabled ontological environment which can play a role in reporting and decision making in Humanitarian Crises (HC). We use (5WH): WHO, WHAT, WHERE, WHEN, WHY and HOW, as the main vehicle for gathering information for decision making. We implement the semantics of (5WH) through OWL models and perform reasoning with SWRL rules, in order to support decision making and create more efficient Humanitarian Response (HR). Our case study shows the feasibility of the proposal and its outcome. © 2012 ISCRAM.
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Aladdin Shamoug, Stephen Cranefield, & Grant Dick. (2018). Information Retrieval for Humanitarian Crises via a Semantically Classified Word Embedding. 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. 132–144). Albany, Auckland, New Zealand: Massey Univeristy.
Abstract: Decision-makers in humanitarian crisis need information to guide them in making critical decisions. Finding information in such environments is a challenging task. Therefore, decision-makers rely on domain experts who possess experience and knowledge from previous humanitarian crises to provide them with the information they need. In this paper, we explore the ability of the existing computing technologies to augment the capabilities of those experts and help decision-makers to make faster and better decisions. Among many computing technologies we have today, word embedding and the semantic web are able to support such augmentation of the domain expert. In this paper, we train a word embedding model using word2vec, transform words and terms from news archive to entities in domain ontology, annotate those entities with their equivalent concepts from upper ontologies, and reason about them using semantic similarity and semantic matching, to represent and retrieve knowledge, and answer questions of interest to decision-makers in humanitarian crises. The approach was evaluated by comparing the use of word embeddings with and without semantic classification for the retrieval of information about the current humanitarian crisis in Syria.
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Alan Aipe, Asif Ekbal, Mukuntha NS, & Sadao Kurohashi. (2018). Linguistic Feature Assisted Deep Learning Approach towards Multi-label Classification of Crisis Related Tweets. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 705–717). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: Micro-blogging site like Twitter, over the last decade, has evolved into a proactive communication channel during mass convergence and emergency events, especially in crisis stricken scenarios. Extracting multiple levels of information associated with the overwhelming amount of social media data generated during such situations remains a great challenge to disaster-affected communities and professional emergency responders. These valuable data, segregated into different informative categories, can be leveraged by the government agencies, humanitarian communities as well as citizens to bring about faster response in areas of necessity. In this paper, we address the above scenario by developing a deep Convolutional Neural Network (CNN) for multi-label classification of crisis related tweets.We augment deep CNN by several linguistic features extracted from Tweet, and investigate their usage in classification. Evaluation on a benchmark dataset show that our proposed approach attains the state-of-the-art performance.
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Alec Pawling, Tim Schoenharl, Ping Yan, & Greg Madey. (2008). WIPER: An emergency response system. In B. V. de W. F. Fiedrich (Ed.), Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management (pp. 702–710). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: This paper describes the WIPER system, a proof of concept prototype, and progress made on its development to date. WIPER is intended to provide emergency response managers with an integrated system that detects possible emergencies from cellular communication data, attempts to predict the development of emergency situations, and provides tools for evaluating possible courses of action in dealing with emergency situations. We describe algorithms for detecting anomalies in streaming cellular communication network data, the implementation of a simulation system that validates running simulations with new real world data, and a web-based front end to the WIPER system. We also discuss issues relating to the real-time aggregation of data from the cellular service provider and its distribution to components of the WIPER system.
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Alena L. Benson, Keith Biggers, Jim Wall, & Mark P. Haselkorn. (2010). Adaptive development of a common operating environment for crisis response and management. 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: Complex information and communication systems present a special challenge to system designers because these are generally deployed as large, distributed systems with diverse user groups. Crisis response and management organizations in particular expect systems to be interoperable, resilient, flexible and provide lasting benefit. Currently, systems such as Virtual USA (Department of Homeland Security) and WatchKeeper (United States Coast Guard) seek to create common situational awareness for all participating agencies in security and incident response operations. We propose adaptive development as a system development model to build upon the ideas of systems such as Virtual USA and WatchKeeper in order to create sustainable and adaptable systems. Adaptive development supports ongoing improvement through user-driven design and modification in the target environment. An internet-based dashboard demonstrated during a United States Coast Guard Sector Seattle incident response exercise serves as an emergent case study for the adaptive model.
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Alessandro Faraotti, Antonella Poggi, Berardino Salvatore, & Guido Vetere. (2009). Information management for crisis response in WORKPAD. In S. J. J. Landgren (Ed.), ISCRAM 2009 – 6th International Conference on Information Systems for Crisis Response and Management: Boundary Spanning Initiatives and New Perspectives. Gothenburg: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: WORKPAD (EU STREP project FP6-2005-IST-5-034749) is an experimental platform for Crisis Response which adopts a decentralized, event-driven approach to overcome problems and limitations of centralized systems. The flexibility of P2P networking is relevant when different organizations must get rapidly integrated the one another, without resorting on standardized ontologies and centralized middleware components. This paper illustrates the main features of the Information Integration platform we've designed. A number of relevant technical and theoretical issues related to decentralized platforms are discussed in the light of specific needs of Crisis Response.
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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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Alessio Malizia, Pablo Acuña, Teresa Onorati, Paloma Díaz, & Ignacio Aedo. (2009). CAP-ONES: An emergency notification system for all. In S. J. J. Landgren (Ed.), ISCRAM 2009 – 6th International Conference on Information Systems for Crisis Response and Management: Boundary Spanning Initiatives and New Perspectives. Gothenburg: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: In this paper we present an ontology-based system for managing emergency alert notifications. Our purpose is to generate emergency alerts that are accessible to different kinds of people, paying special attention to more vulnerable collectives like impaired people. By adapting alerts to different devices and users we can allow Emergency Management Systems (EMS) to communicate with collectives like blind or deaf people whom otherwise will be unreachable by usual channels. Moreover, if we consider the constrains imposed by the nature of the emergency situations we can also improve the information transmission to cope with situational disabilities (e.g. smoke during a fire can cause low vision problems). We centered our system architecture on two characteristics: The first one is an ontology that codifies knowledge about accessibility, devices, disabilities, emergencies and media so the alert notification can be tailored according to different parameters; the second one is the use of an open standard like the CAP (Common Alerting Protocol) that enables our system to interoperate with other existing systems.
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Alexander Smirnov, Nikolay Shilov, Tatiana Levashova, & Alexey Kashevnik. (2008). Web-service network for disaster management. In B. V. de W. F. Fiedrich (Ed.), Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management (pp. 516–525). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: The paper addresses the issue of context-aware operational decision support in emergency situations. A decision support system (DSS) developed for this purpose is implemented as a network of a set of Web-services. The Web-services try to organise a service network according to context. Here the context is proposed to be modelled as a “problem model”. It specifies problems to be solved in a particular kind of emergency situation. Context is produced based on the knowledge extracted from the application domain (application ontology) and formalised by a set of constraints. The purpose of the service network is provision the DSS with contextualised information from diverse information sources and solving problems specified in the context. In the framework of context-aware operational decision support, composition of the application ontology for the disaster management domain from the Semantic Web Ontologies is discussed and a hybrid technology of context-aware operational decision support is presented. The technology is based on ontology management, context management, constraint satisfaction, and Web Services. Application of the ideas above is illustrated by an example of a decision support system for real-time resource coordination and situation awareness for logistics management in fire response operations.
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Alexander Smirnov, Tatiana Levashova, & Nikolay Shilov. (2013). Context-based knowledge fusion patterns in decision support system for emergency response. In J. Geldermann and T. Müller S. Fortier F. F. T. Comes (Ed.), ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management (pp. 597–606). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: The purpose of this paper is discovery of context-based knowledge fusion patterns. Knowledge fusion is considered as an appearance of new knowledge in consequence of processes ongoing in decision support systems. The knowledge fusion processes are considered within a system intended to support decisions on planning emergency response actions. The knowledge fusion patterns are generalized with regard to preservation of internal structures and autonomies of information and knowledge sources involved in the knowledge fusion and to knowledge fusion results. The found patterns give a general idea of knowledge fusion processes taking place at the operational stage of decision support system functioning, i.e. the stage where context-aware functions of the system come into operation. As a practical application, such patterns can support engineers with making choice of knowledge sources to be used in the systems they design.
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Alexander Smirnov, Tatiana Levashova, & Nikolay Shilov. (2010). Ubiquitous computing in emergency: Profile-based situation response. In C. Zobel B. T. S. French (Ed.), ISCRAM 2010 – 7th International Conference on Information Systems for Crisis Response and Management: Defining Crisis Management 3.0, Proceedings. Seattle, WA: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Ubiquitous computing opens new possibilities to various aspects of human activities. The paper proposes an approach to emergency situation response that benefits of the ubiquitous computing. The approach is based on utilizing profiles to facilitate the coordination of the activities of the emergency response operation members. The major idea behind the approach is to represent the operation members together with information sources as a network of services that can be configured via negotiation of participating parties. Such elements as profile structure, information source model and negotiation protocol are described in detail.
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Alexander Staves, Harry Balderstone, Benjamin Green, Antonios Gouglidis, & David Hutchison. (2020). A Framework to Support ICS Cyber Incident Response and Recovery. 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. 638–651). Blacksburg, VA (USA): Virginia Tech.
Abstract: During the past decade there has been a steady increase in cyber attacks targeting Critical National Infrastructure. In order to better protect against an ever-expanding threat landscape, governments, standards bodies, and a plethora of industry experts have produced relevant guidance for operators in response to incidents. However, in a context where safety, reliability, and availability are key, combined with the industrial nature of operational systems, advice on the right practice remains a challenge. This is further compounded by the volume of available guidance, raising questions on where operators should start, which guidance set should be followed, and how confidence in the adopted approach can be established. In this paper, an analysis of existing guidance with a focus on cyber incident response and recovery is provided. From this, a work in progress framework is posited, to better support operators in the development of response and recovery operations.
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Alexandra Krakovsky. (2010). The role of social networks in crisis situations: Public participation and information exchange. In C. Zobel B. T. S. French (Ed.), ISCRAM 2010 – 7th International Conference on Information Systems for Crisis Response and Management: Defining Crisis Management 3.0, Proceedings. Seattle, WA: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: The goal of the paper is to discuss the framework for an interdisciplinary human-computer interactive technology that facilitates information and resource exchange and forms core groups for crisis management. The social networks discussed here are designed to incorporate local knowledge and participation and to foster institutional and academic ties by modeling interrelationships among global communities and exploring policy options. Social interactions between individuals and organizations are explored especially in situations when directed responses are helpful in predicting the complex interplay between social, political, and technological systems and practices that result in a transfer of information and resources in disaster situations. In the future, such networks shall identify patterns through which groups interact in responding to critical issues and shall incorporate more complicated actions by individuals and organizations allowing them to move away from a rigid path to manage disasters via the most situationally appropriate routes.
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Ali Khalili-Araghi, Uwe Glässer, Hamed Yaghoubi Shahir, Brian Fisher, & Piper Jackson. (2012). Intelligent decision support for emergency responses. 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: With a coastline touching upon the Pacific and Atlantic Oceans, the Great Lakes and the Arctic Sea, the Canadian MSOCs are faced with a daunting task. They are responsible for both routine duties, including patrolling coastal areas and collecting satellite data, as well as critical missions, such as emergency response and crime intervention. Both kinds of mission require the fusion of data from a variety of sources and the orchestration of myriad heterogeneous resources over great physical distances. They must deal with uncertainty, both in terms of what can be known and also in the outcomes of actions, and must interact with an environment prone to dynamic change. We present the architecture and core mechanisms of a decision support system for marine safety and security operations (Glässer, Jackson, Araghi, When and Shahir, 2010). The goal of this system is to enhance complex command and control tasks by improving situational awareness and automating task assignments. This system concept includes adaptive information fusion techniques integrated with decentralized control mechanisms for dynamic resource configuration management and task execution management under uncertainty. Autonomously operating agents employ collaboration and coordination to collectively form an intelligent decision support system. © 2012 ISCRAM.
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Alkusaibati, W., & Pilemalm, S. (2023). Digitalized Co-production and Volunteerism in Emergency Response: a Literature Review. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 738–750). Omaha, USA: University of Nebraska at Omaha.
Abstract: ICT-enabled or digitalized co-production of public services has become increasingly relevant to emergency response and crisis management. This study provides a literature review on this phenomenon, exploring both large-scale crises and frequent emergencies. We found that research in the domain is scarce and focuses mainly on the phenomenon in terms of digital volunteerism. In large-scale crises, they mostly refer to spontaneous forms of volunteering, and in smaller emergencies, to more organized volunteers that collaborate with a response organization over time. Similarities to digitalized co-production in the public sector generally include financial, administrative, ICT, and demographic factors. Differences include, e.g., aspects of coordination, support, and processing by formal actors. We argue that there are benefits of adding a theoretical co-production perspective to digital volunteerism in emergency response and that our literature review can guide future research on models and (the double) use of volunteers in both kinds of emergencies.
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Amanda L. Hughes, Leysia Palen, Jeannette N. Sutton, Sophia B. Liu, & Sara Vieweg. (2008). Site-seeing in disaster: An examination of on-line social convergence. In B. V. de W. F. Fiedrich (Ed.), Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management (pp. 324–333). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: On-line websites and applications are increasingly playing a role in disaster response and recovery. Yet with the wide variety of on-line grassroots activities that occur in such situations, it can be difficult to make sense of them. In this paper, we describe on-line behavior as socially convergent activity, interpreting it within existing sociological understandings of behavior in disaster events. We discuss seven types of convergent behavior and give examples of on-line activities for each type. By seeing these activities as an essential part of the disaster social arena, we can begin to think about how to support socially convergent phenomena in new and creative ways.
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Ana C. Calderon, Joanne Hinds, & Peter Johnson. (2014). IntCris: A tool for enhanced communication and collective decision-making during crises. 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. 205–214). University Park, PA: The Pennsylvania State University.
Abstract: Responding to a large-scale disaster such as an earthquake or hurricane is a collective problem. Human agents are increasingly collaborating with non-human agents (autonomous systems) in attempt to respond to a disaster. IntCris is a prototype intended to bring together interaction for human and non-human agents to aid the decision-making process by focusing on how to facilitate the “correct information to the correct agent” problem as well as encouraging new and agile behaviour. We focus on three categories of information: command, report and personal with a formal grammar to accompany the implementation. The requirements for the software were inspired by real life case studies from Hurricane Katrina, the Fukoshima Nuclear Disaster and Hurricane Sandy. The contribution of this work is to advance technology that brings together HAS (human and autonomous system interaction), in addition to enhancing collective intelligence.
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