Yaniv Mordecai, & Boris Kantsepolsky. (2018). Intelligent Utilization of Dashboards in Emergency Management. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 1108–1119). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: Effective decision-supporting visualization is critical for strategic, tactic, and operational management before and during a large-scale climate or extreme weather emergency. Most emergency management applications traditionally consist of map-based event and object visualization and management, which is necessary for operations, but has small contribution to decision makers. At the same time, analytical models and simulations that usually enable prediction and situation evaluation are often analyst-oriented and detached from the operational command and control system. Nevertheless, emergencies tend to generate unpredictable effects, which may require new decision-support tools in real-time, based on alternative data sources or data streams. In this paper, we advocate the use of dashboards for emergency management, but more importantly, we propose an intelligent mechanism to support effective and efficient utilization of data and information for decision-making via flexible deployment and visualization of data streams and metric displays. We employ this framework in the H2020 beAWARE project that aims to develop and demonstrate an innovative framework for enhanced decision support and management services in extreme weather climate events.
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Xiang Yao, & Murray Turoff. (2007). Using task structure to improve Collaborative Scenario Creation. 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. 591–594). Delft: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: This paper provides a task structure design for collaborative scenario elicitation. Task structure design is part of this effort to design a new Collaborative Scenario Creation (CSC) system. The complexity of the scenario creation process hinders participants, especially novice participants, from prudently designing scenarios. Research in Group Decision Support Systems (GDSS) shows that task structure helps to improve processes and collaborations. To design task structure for collaborative scenario elicitation, this paper invokes the Entity-Relationship data modeling methodology.
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Xiang Yao, Murray Turoff, & Michael J. Chumer. (2009). Designing a group support system to review and practice emergency plans in virtual teams. 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 the 21st century, rapid changes of our society necessitate continuous review and practice of emergency plans. Traditional face-to-face (FtF) interactions to make emergency plans and train responders seem insufficient. The virtual team (VT), a new team form allowing dynamic recruitment of experts from global extent and conduction of teamwork whenever it is needed, provides a more agile solution. This paper introduces a group support system called Collario (Collaborative Scenario) aiming to facilitate effective collaboration in creating and discussing scenarios in VTs and to utilize scenarios as the vehicle to review and practice emergency plans on a continuous basis. This research is still in progress. Three professionals have been involved in system demonstrations and interviews. Although it is still too early to make any conclusions, it is encouraging to know that all the three experts thought Collario easy to use and might be useful for various emergency preparedness purposes.
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Yikun Liu, Sung Pil Moon, Mark Pfaff, Jill L. Drury, & Gary L. Klein. (2011). Collaborative option awareness for emergency response decision making. In E. Portela L. S. M.A. Santos (Ed.), 8th International Conference on Information Systems for Crisis Response and Management: From Early-Warning Systems to Preparedness and Training, ISCRAM 2011. Lisbon: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: We have been using exploratory modeling to forecast multiple plausible outcomes for a set of decision options situated in the emergency response domain. Results were displayed as a set of box-plots illustrating outcome frequencies distributed across an evaluative dimension (e.g., cost, score, or utility). Our previous research showed that such displays provide what we termed “option awareness” – an ability to determine robust options that will have good outcomes across the broadest number of plausible futures. This paper describes an investigation into extending this approach to collaborative decision making by providing a visualization of both collaborative and individual decision spaces. We believe that providing such visualizations will be particularly important when each individuals decision space does not account for the synergy that may emerge from collaboration. We describe how providing collaborative decision spaces improves the robustness of joint decisions and engenders high confidence in these decisions.
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Nan Zhang, Clare Bayley, & Simon French. (2008). Use of web-based group decision support for crisis 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. 55–58). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Web-based group decision support systems (wGDSS) are becoming more common in organizations. In this paper, we provide a review and critique of the literature on wGDSS, raising a number of issues that need addressing. Then we report on a small scale experiment using Groupsystems ThinkTank to manage an issue to do with food safety. We also describe how we propose to use ThinkTank in a crisis situation.
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Andrea Zielinski, Stuart E. Middleton, Laurissa N. Tokarchuk, & Xinyue Wang. (2013). Social media text mining and network analysis for decision support in natural crisis 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. 840–845). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: A core issue in crisis management is to extract from the mass of incoming information what is important for situational awareness during mass emergencies. Based on a case study we develop a prototypical application, TweetComp1, which is integrated into the decision-support component of a Tsunami early warning system and demonstrates the applicability of our approach. This paper describes four novel approaches using focused twitter crawling, trustworthiness analysis, geo-parsing, and multilingual tweet classification in the context of how they could be used for monitoring crises. The validity of our state-of-the art text mining and network analysis technologies will be verified in different experiments based on a human annotated gold standard corpus.
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Christopher W. Zobel. (2010). Comparative visualization of predicted disaster resilience. 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 disaster resilience triangle is a simple but effective tool for illustrating the relationship between the initial impact of a disaster event and the subsequent time to recovery. This tool can also be expanded, however, to provide an analytic measure of the level of resilience exhibited by a particular entity in a given disaster situation. We build upon the previous work in this area by developing a new approach for visualizing and analyzing the tradeoffs between the two primary defining characteristics of the disaster resilience triangle. This new approach supports strategic decision making in a disaster planning environment by providing a straightforward means for directly comparing the relative predicted resilience of different critical facilities within an organization, with respect to both location and type of risk.
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