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Nitesh Bharosa, Sebastiaan Meijer, Marijn Janssen, & Fritjof Brave. (2010). Are we prepared? Experiences from developing dashboards for disaster preparation. 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: Relief agency managers show growing interest in dashboards for assessing multi-agency disaster preparedness. Yet, there is a dearth of research on the development and use of dashboards for disaster preparation. Consequently, information system architects in the disaster management domain have little guidance in developing dashboards. Here, dashboards refer to digitalized visualizations of performance indicators. In this paper, we discuss the experiences gained from an action research project on the development of dashboards for assessing disaster preparedness. The objective of this paper is to discuss experiences and tradeoffs extracted from the development of dashboards in practice. We organized a two-day gaming-simulation with relief agency managers for the evaluation of the dashboards. While the relief agency managers acknowledged the usefulness of dashboards in the disaster preparation process and expressed their intention to use these in practice, they suggested that the formulation and clustering of performance indicators requires further research.
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Bruno S. N., Adriana S. Vivacqua, & Marcos R.S. Borges. (2016). A Conceptual Architecture to handle the influx of information in Emergency Situations. 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: Emergency situations are characterized by their complexity and the heterogeneity of the available information. Emergency managers are frequently confronted with redundant or irrelevant information, causing the problem of information overload. Evidence of this problem was identified in an exploratory survey conducted in the Center for Integrated Command and Control of Rio de Janeiro (CICC-RJ). In this paper, we present a conceptual architecture that allows a user to handle this influx of information. From a set of available data, a manager can select those of interest, which can then be transformed and mapped into one or more views, and organized in a dashboard. The whole process is interactive, allowing the manager to redefine his/her dashboard as needed. In addition, we provide collaborative mechanisms, given that, at times, it is not possible for a single user to handle such large datasets alone.
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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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