Bryan Semaan, Gloria Mark, & Ban Al-Ani. (2010). Developing information technologies for citizens experiencing disruption: The role of trust and context. In C. Zobel B. T. S. French (Ed.), ISCRAM 2010 – 7th International Conference on Information Systems for Crisis Response and Management: Defining Crisis Management 3.0, Proceedings. Seattle, WA: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: This paper considers a subset of the technology-enabled communication that took place among citizen populations experiencing various disruptions, e.g. disaster and war. In the context of a disrupted environment, trust can erode where people no longer rely on institutions for support (i.e. the government), or where citizens do not trust other people. We argue that depending on what is taking place in the physical world, trust in people, information, and institutions can change – in this sense, trust is contextual. We then offer recommendations for designing new technologies for people who experience disruption, taking into account trust and context.
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Alexander Smirnov, Mikhail Pashkin, Nikolay Shilov, & Tatiana Levashova. (2007). Intelligent support of context-based megadisaster management: Hybrid technology and case study. In K. Nieuwenhuis P. B. B. Van de Walle (Ed.), Intelligent Human Computer Systems for Crisis Response and Management, ISCRAM 2007 Academic Proceedings Papers (pp. 305–316). Delft: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: The situation with the hurricane Katrina showed that the conventional tiered response to disaster event, whereby state and local officials are responsible for the first few days, does not work well in case of megadisasters (massive hurricanes, earthquakes, large-scale acts of terrorism, etc.). Such situations require application of new technologies for preparing the operation, interoperability between the operation participants, and decision support for officials. Here presented approach proposes a context-driven decision support schema based on integration of such technologies as context & ontology management and constraint satisfaction. The application of the approach is illustrated via a case study of a portable hospital arrangement.
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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, Andrew Krizhanovsky, Nikolay Shilov, & Alexey Kashevnik. (2009). Self-organizing resource network for traffic accident response. 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: Traffic accidents are a common feature of the modern life. The paper proposes an approach addressing response to traffic accidents happened in a smart environment. The idea behind the approach is to self-organize resources of the environment according to the state of the situation caused by the accident. The resources self-organize a collaborative network that comprises physical devices, software services, organizations, and persons. The purpose of the resources is to undertake joint actions for accident response. The disaster response system intended for operating in smart environments has a service-oriented architecture. Some of Web-services making up the architecture are intended to model the accident situations; others model resource functionalities or bear supporting functions. Web-services that model resource functionalities are aligned against the disaster management ontology. This alignment ensures semantic interoperability of the heterogeneous resources. The alignment operation is supported by a tool that identifies similar concepts in the ontology and Web-service descriptions using a machine-readable dictionary. Response to the traffic accident illustrates main ideas described in the paper.
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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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Sofia Eleni Spatharioti, Sara Wylie, & Seth Cooper. (2018). Does Flight Path Context Matter? Impact on Worker Performance in Crowdsourced Aerial Imagery Analysis. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 621–628). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: Natural disasters result in billions of dollars in damages annually and communities left struggling with the difficult task of response and recovery. To this end, small private aircraft and drones have been deployed to gather images along flight paths over the affected areas, for analyzing aerial photography through crowdsourcing. However, due to the volume of raw data, the context and order of these images is often lost when reaching workers. In this work, we explored the effect of contextualizing a labeling task on Amazon Mechanical Turk, by serving workers images in the order they were collected on the flight and showing them the location of the current image on a map. We did not find a negative impact from the loss of contextual information, and found map context had a negative impact on worker performance. This may indicate that ordering images based on other criteria may be more effective.
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Evan A. Sultanik, & Clayton Fink. (2012). Rapid geotagging and disambiguation of social media text via an indexed gazetteer. 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: Microblogging services like Twitter afford opportunities for real time determination of situation awareness during crises as people report, via their statuses, information about events on the ground. An important component of the information included in a tweet are mentions of place names that may be sites of damage, injuries, or relief efforts. Methods for extracting these place names and determining the actual location being referenced are an essential part of the suite of tools required for automated extraction of situation awareness from tweets. Extracting and disambiguating place name mentions from text have been areas of extensive research. Twitter, however, presents challenges given the 140 character restriction on status and the informal, abbreviated language that are a norm in this communication channel. Named entity recognizers, which are dependent on labeled training data, may not be useful in this medium for extracting location mentions because the typical training domains for these taggers are absent the noise found in Twitter statuses. Additionally, the contextual information that is necessary for disambiguating place names is not always present. In this paper, we demonstrate a new technique, RapidGeo, for extracting and disambiguating place names from a location specific Twitter feed using an unsupervised technique for tagging location mentions and relying on the known geographic context of the feed for disambiguation. Our location tagging technique performs much better than an off-the-shelf named entity recognizer and we achieve reasonable precision in disambiguating extracted place names. We argue that such fast, high precision, unsupervised approaches are needed when important, actionable information is required from noisy data sources such as Twitter. © 2012 ISCRAM.
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Elena Tsiporkova, Nicolás González-Deleito, Tom Tourwé, & Anna Hristoskova. (2012). Ontology-driven multimodal interface design for an emergency response application. 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 propose an ontology-driven modelling framework, which allows to capture the domain and expert knowledge available within the interface design community, and to support designers in their daily design tasks by eliciting user and application dependent design recommendations. We illustrate how this framework can be used in practice with a concrete case study devoted to multimodal interface design for the purpose of emergency response applications. © 2012 ISCRAM.
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Valentin Barriere, & Guillaume Jacquet. (2021). How does a Pre-Trained Transformer Integrate Contextual Keywords? Application to Humanitarian Computing. In Anouck Adrot, Rob Grace, Kathleen Moore, & Christopher W. Zobel (Eds.), ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management (pp. 766–771). Blacksburg, VA (USA): Virginia Tech.
Abstract: In a classification task, dealing with text snippets and metadata usually requires to deal with multimodal approaches. When those metadata are textual, it is tempting to use them intrinsically with a pre-trained transformer, in order to leverage the semantic information encoded inside the model. This paper describes how to improve a humanitarian classification task by adding the crisis event type to each tweet to be classified. Based on additional experiments of the model weights and behavior, it identifies how the proposed neural network approach is partially over-fitting the particularities of the Crisis Benchmark, to better highlight how the model is still undoubtedly learning to use and take advantage of the metadata's textual semantics.
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Willem Van Santen, Catholijn M. Jonker, & Niek Wijngaards. (2009). Crisis decision making through a shared integrative negotiation mental model. 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: Decision making during crises takes place in (multi-agency) teams, in a bureaucratic political context. As a result, the common notion that during crises decision making should be done in line with a Command & Control structure is invalid. This paper shows that the best way for crisis decision making teams in a bureaucratic political context is to follow an integrative negotiation approach as the shared mental model of decision making. This conclusion is based on an analysis of crisis decision making by teams in a bureaucratic political context. First of all this explains why in a bureaucratic political context the Command & Control adage does not hold. Secondly, this paper motivates why crisis decision making in such context can be seen as a negotiation process. Further analysis of the given context shows that an assertive and cooperative approach suits crisis decision making best.
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Beth Veinott, Gary L. Klein, & Sterling Wiggins. (2010). Evaluating the effectiveness of the PreMortem technique on plan confidence. 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: One problem affecting crisis management planning teams is overconfidence- An inflated belief that a plan will be successful. In this paper we compared the effect of several different methods for reducing individual team member confidence levels and compared each to a baseline control condition. One hundred and seventy-eight people participated in one of five conditions to evaluate an H1N1 flu epidemic plan in a university context. Over the course of evaluating the plan, participants provided several ratings of confidence in the plan's success and their understanding. We compared several techniques commonly used, such as critique, Pro/Cons generation, Cons only generation and a newer technique, PreMortem, to a baseline condition. The Pro/Cons generation, Cons only generation and the PreMortem technique all reliably reduced confidence levels more than baseline condition. Furthermore, the Premortem method, imagining that a plan has failed and then generating reasons to explain why, reliably reduced confidence more than each of the other conditions, and therefore can be a useful tool for combating overconfidence in crisis management planning. We discuss the results in the context of sensemaking and decision making theory.
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Steven C. Way, & Yufei Yuan. (2012). Towards a context-aware multi-party emergency coordination system framework. 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: A framework for an emergency response system is proposed which is an extension of, but significantly different from, traditional group and distributed group support systems. The framework considers the environmental, organizational, and activity-based issues of emergency response for responders and decision makers. These issues are addressed by incorporating context-aware, multi-agency relationship management, and multiparty coordination components into the framework for a context-aware multiparty coordination system. © 2012 ISCRAM.
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Zhenke Yang, & Leon J.M. Rothkrantz. (2007). Emotion sensing for context sensitive interpretation of crisis reports. In K. Nieuwenhuis P. B. B. Van de Walle (Ed.), Intelligent Human Computer Systems for Crisis Response and Management, ISCRAM 2007 Academic Proceedings Papers (pp. 507–514). Delft: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: The emotional qualities of a report play an important role in the evaluation of eye witness reports in crisis centers. Human operators in the crisis center can use the amount of anxiety and stress detected in a spoken report to rapidly estimate the possible impact and urgency of a report and the appropriate response to the reporter. This paper presents ongoing work in automated multi-modal emotion sensing of crisis reports in order to reduce the cognitive load on human operators. Our approach is based on the work procedures adopted by the crisis response center Rijnmond environmental agency (DCMR) and assumes a spoken dialogue between a reporter and a crisis control center. We use an emotion model based on conceptual graphs that is continually evaluated while the dialogue continues. We show how the model can be applied to interpret crisis report in a fictional toxic gas dispersion scenario.
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