Brian M. Tomaszewski, Anthony C. Robinson, Chris E. Weaver, Michael Stryker, & Alan M. MacEachren. (2007). Geovisual analytics and crisis management. 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. 173–179). Delft: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Increasing data heterogeneity, fragmentation and volume, coupled with complex connections among specialists in disaster response, mitigation, and recovery situations demand new approaches for information technology to support crisis management. Advances in visual analytics tools show promise to support time-sensitive collaboration, analytical reasoning, problem solving and decision making for crisis management. Furthermore, as all crises have geospatial components, crisis management tools need to include geospatial data representation and support for geographic contextualization of location-specific decision-making throughout the crisis. This paper provides an introduction to and description of Geovisual Analytics applied to crisis management activity. The goal of Geovisual Analytics in this context is to support situational awareness, problem solving, and decision making using highly interactive, visual environments that integrate multiple data sources that include georeferencing. We use an emergency support function example to discuss how recent progress in Geovisual Analytics can address the issues a crisis can present.
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Bruce D. Campbell, Konrad E. Schroder, & Chris E. Weaver. (2010). RimSim visualization : An interactive tool for post-event sense making of a first response effort. 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: Upon developing a software agent-based simulator for training roles in emergency response scenarios, the PARVAC team at the University of Washington has pursued building a tool for better investigative review and insight generation on the performance of an emergency response game session team. While our RimSim Response software included the opportunity to re-run a simulated team performance in order to review player and agent behavior, we did not provide our trainees the ability to visually query their performance outside of a sequential review of the emergency response effort. By integrating our RSR visualization components with an existing visual query software package called Improvise, we were able to construct highly-coordinated visualizations of our data model for the ability to apply a sense making approach in the investigation of live player and software agent-based behavior – both as individual players and as combinations of players working on tasks associated with an emergency response scenario. The resultant tool is now our primary visualization tool for discussing first responder team performance and supports the overall RSR objective of training teams to make the most effective, recognition-primed decisions when a real emergency crisis occurs in their community. This paper reviews our visualization tool and demonstrates its use.
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