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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Linn Marks Collins, James E. Powell Jr., Carolyn E Dunford, Ketan K. Mane, & Mark L.B. Martinez. (2008). Emergency information Synthesis and awareness using E-SOS. In B. V. de W. F. Fiedrich (Ed.), Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management (pp. 618–623). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: In an emergency, people need to be able to report and find relevant information quickly. Fulfilling these information needs is the design goal of E-SOS: Emergency Situation Overview and Synthesis, a research project in progress. E-SOS will consist of (1) a website where users can report information, (2) web services that find and synthesize related information from multiple sources, and (3) interface tools that visualize and display links to this information. In this paper we describe three of these services and tools: the topic, geographic, and information space awareness tools. When a user writes a report, the topic awareness tool will execute a federated search and display links to related information. The information space awareness tool will highlight these links in a visualization of the information space. If the user refers to a location, the geographic awareness tool will focus a map on this location and display topic-related icons.
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Matthias Lendholt, Martin Hammitzsch, & Peter Löwe. (2013). Harmonization of data formats for tsunami simulation products. 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. 365–369). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: The development of sustainable tsunami early warning systems (TEWS) requires the adoption of proven standards for components on all system levels. This is crucial to ensure the successful operation of the overall system in the long term. Currently, components, data formats and models used to build an individual TEWS come from independent development efforts, using non-standardized proprietary interfaces. Integrating these components into a TEWS requires additional work effort due to the proprietary technologies and formats. This article discusses alternative cost-effective approaches. The successful integration of the TEWS system components depends critically on the adoption and application of industry standards and good practices. From this perspective, this article examines the role of tsunami simulation models, and the challenge to integrate the data products generated from independent tsunami models for a TEWS. The significance of tsunami simulation products, consisting of data and metadata, for the overall early warning workflow is described, including data exchange (among multiple TEWS) and information visualization in combination with additional spatial information. As an outcome, the use of standardized data formats for simulation products is recommended for future work. This approach is demonstrated on a simulation of the March 2011 Tohoku-Oki mega thrust earthquake.
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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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Sung Pil Moon, Yikun Liu, Steven O. Entezari, Afarin Pirzadeh, Andrew Pappas, & Mark Pfaff. (2013). Top health trends: An information visualization tool for awareness of local health trends. 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. 177–187). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: We developed an intelligent information visualization tool to enable public health officials to detect healthrelated trends in any geographic area of interest, based on Twitter data. Monitoring emergent events such as natural disasters, disease outbreaks, and terrorism is vital for protecting public health. Our goal is to support situation awareness (SA) for personnel responsible for early detection and response to public health threats. To achieve this goal, our application identifies the most frequently tweeted illnesses in a ranked chart and map for a selected geographic area. Automated processes mine and filter health-related tweets, visualize changes in rankings over time, and present other keywords frequently associated with each illness. User-centered visualization techniques of monitoring, inspecting, exploring, comparing and forecasting supports all the three stages of SA. An evaluation conducted with experts in health-related domains provided significant insights about awareness of localized health trends and their practical use in their daily work.
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