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Christine M. Newlon, Mark Pfaff, Himalaya Patel, Gert-Jan De Vreede, & Karl MacDorman. (2009). Mega-collaboration: The Inspiration and development of an interface for large-scale disaster 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: The need to gather and use decentralized information and resources in responding to disasters demands an integrated interface that can support large-scale collaboration. This paper describes the development of a collaboration tool interface. The tool will surpass existing groupware and social networking applications, providing easy entry, categorization, and visualization of masses of critical data; the ability to form ad-hoc teams with collaboration protocols for negotiated action; and agent-augmented mixed-initiative tracking and coordination of these activities. The paper reports user testing results concerning the data entry interface, emergent leadership, and the directed negotiation process. The paper also discusses planned enhancements, including formalized collaboration engineering and the use of a disaster simulation test bed.
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Jennifer Mathieu, Mark Pfaff, Gary L. Klein, Jill L. Drury, Michael Geodecke, John James, et al. (2010). Tactical robust decision-making methodology: Effect of disease spread model fidelity on option awareness. 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: We demonstrate a method of validating the utility of simpler, more agile models for supporting tactical robust decision making. The key is a focus on the decision space rather than the situation space in decision making under deep uncertainty. Whereas the situation space is characterized by facts about the operational environment, the decision space is characterized by a comparison of the options for action. To visualize the range of options available, we can use computer models to generate the distribution of plausible consequences for each decision option. If we can avoid needless detail in these models, we can save computational time and enable more tactical decision-making, which will in turn contribute to more efficient Information Technology systems. We show how simpler low fidelity, low precision models can be proved to be sufficient to support the decision maker. This is a pioneering application of exploratory modeling to address the human-computer integration requirements of tactical robust decision making.
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Jill L. Drury, Gary L. Klein, Jennifer Mathieu, Yikun Liu, & Mark Pfaff. (2013). Sympathetic decisions: Incorporating impacts on others into emergency response decision spaces. 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. 199–209). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: We designed two decision support tools and employed them during a one-week, simulation-driven experiment that included emergency responders acting in their real-life roles. Each tool visualized a “decision space”: A diagrammatic depiction of the relative desirability of one option versus another, including the inherent uncertainty in the potential outcomes. One requirement was to develop a tool accounting for the impacts of decisions on others, so that emergency responders can make “sympathetic decisions.” For example, one decision space enabled responders to request resources from surrounding jurisdictions while also considering the potential negative effects on the lending organizations. Another decision space enabled responders to engage in a strategic dialogue with the public: “listening” to the public's greatest concerns by mining social media to measure emotion, and thereby suggesting strategic communications addressing those concerns. We report how we designed the decision spaces and the qualitative results of using these spaces during the experiment.
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Jill L. Drury, Gary L. Klein, Mark Pfaff, & Steven O. Entezari. (2012). Establishing collaborative option awareness during crisis management. 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: This paper presents empirical results of the use of a novel decision support prototype for emergency response situations, which was designed to enhance the understanding of the relative desirability of one potential course of action versus another. We have termed this understanding “option awareness.” In particular, this paper describes the process employed by pairs of experiment participants while performing emergency responder roles using different types of “decision space” visualizations to help them collaborate on decisions. We examined the decision making process via a detailed analysis of the communication between the cooperating team members. The results yield implications for design approaches for visualizing option awareness. © 2012 ISCRAM.
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Jill L. Drury, Loretta More, Mark Pfaff, & Gary L. Klein. (2009). A principled method of scenario design for testing emergency response decision-making. 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: We are investigating decision aids that present potential courses of action available to emergency responders. To determine whether these aids improve decision quality, however, we first developed test scenarios that were challenging in well-understood ways to ensure testing under the full breadth of representative decision-making situations. We devised a three-step method of developing scenarios: define the decision space, determine the cost components of each decision's potential consequences based on the principles of Robust Decision Making, then choose conflicting pairs of cost components (e.g., a small fire, implying low property damage, in a densely inhabited area, which implies high personal injury). In a validation of this approach, experiment participants made decisions faster in non-ambiguous cases versus cases that included this principled introduction of ambiguity. Our Principled Ambiguity Method of scenario design is also appropriate for other domains as long as they can be analyzed in terms of costs of decision alternatives.
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Starr Roxanne Hiltz, Mark Pfaff, Linda Plotnick, & Patrick C. Shih. (2014). Message from the Conference program (Co-)Chairs. In and P.C. Shih. L. Plotnick M. S. P. S.R. Hiltz (Ed.), ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management (pp. 5–6). University Park, PA: The Pennsylvania State University.
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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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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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