Simone De Kleermaeker, & Jan Verkade. (2013). A decision support system for effective use of probability forecasts. 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. 290–295). KIT; Baden-Baden: Karlsruher Institut fur Technologie. Abstract: Often, water management decisions are based on hydrological forecasts, which are affected by inherent uncertainties. It is increasingly common for forecasters to make explicit estimates of these uncertainties. Associated benefits include the decision makers' increased awareness of forecasting uncertainties and the potential for risk-based decision-making. Also, a more strict separation of responsibilities between forecasters and decision maker can be made. A recent study identified some issues related to the effective use of probability forecasts. These add a dimension to an already multi-dimensional problem, making it increasingly difficult for decision makers to extract relevant information from a forecast. Secondly, while probability forecasts provide a necessary ingredient for risk-based decision making, other ingredients may not be fully known, including estimates of flood damage and costs and effect of damage reducing measures. Here, we present suggestions for resolving these issues and the integration of those solutions in a prototype decision support system (DSS). A pathway for further development is outlined. Keywords: Artificial intelligence; Decision support systems; Forecasting; Hydrology; Information systems; Uncertainty analysis; Water management; Decision support system (dss); Hydrological forecast; Management decisions; Multidimensional problems; Predictive uncertainty; Probabilistic forecasts; Probability forecasts; Risk-based decisions; Decision making Track: Decision Support Systems Share to FB \| Save citation: RTF PDF LaTeX \| Export record: Atom XML MODS XML OAI_DC XML ODF XML SRW_DC XML SRW_MODS XML
Milica Stojmenovic, & Gitte Lindgaard. (2014). Probing PROBE: A field study of an advanced decision support prototype for managing chemical, biological, radiological, nuclear, and explosives (CBRNE) events. 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. 90–99). University Park, PA: The Pennsylvania State University. Abstract: The purpose of this field study was investigate teamwork and communication among event management personnel, to assess the degree to which PROBE, the advanced prototype they were using to manage a CBRNE simulation, would adequately meet their needs. The study was a continuation of previous research conducted in the early phase of PROBE development. Two communication-related analyses were applied to identify instances of effective and of ineffective communication among the management team. These revealed that communication was mostly effective. However, the one serious communication breakdown that was observed could have had fatal consequences. It showed that great care must be taken to ensure the safety of first responders at all times when evaluating prototypes in the field. A list of questions was generated from the lessons learned to assist future researchers prepare for CBRNE field studies. Keywords: Artificial intelligence; Communication; Decision support systems; Information systems; Probes; Chemical; biological; radiological; nuclear; Communication breakdowns; Decision supports; Event management; First responders; Management decisions; Management team; Teamwork; Human resource management Track: Command and Control Studies Share to FB \| Save citation: RTF PDF LaTeX \| Export record: Atom XML MODS XML OAI_DC XML ODF XML SRW_DC XML SRW_MODS XML

Abstract: Often, water management decisions are based on hydrological forecasts, which are affected by inherent uncertainties. It is increasingly common for forecasters to make explicit estimates of these uncertainties. Associated benefits include the decision makers' increased awareness of forecasting uncertainties and the potential for risk-based decision-making. Also, a more strict separation of responsibilities between forecasters and decision maker can be made. A recent study identified some issues related to the effective use of probability forecasts. These add a dimension to an already multi-dimensional problem, making it increasingly difficult for decision makers to extract relevant information from a forecast. Secondly, while probability forecasts provide a necessary ingredient for risk-based decision making, other ingredients may not be fully known, including estimates of flood damage and costs and effect of damage reducing measures. Here, we present suggestions for resolving these issues and the integration of those solutions in a prototype decision support system (DSS). A pathway for further development is outlined.

Keywords: Artificial intelligence; Decision support systems; Forecasting; Hydrology; Information systems; Uncertainty analysis; Water management; Decision support system (dss); Hydrological forecast; Management decisions; Multidimensional problems; Predictive uncertainty; Probabilistic forecasts; Probability forecasts; Risk-based decisions; Decision making

Track: Decision Support Systems

| Save citation: RTF PDF LaTeX

| Export record: Atom XML MODS XML OAI_DC XML ODF XML SRW_DC XML SRW_MODS XML

Abstract: The purpose of this field study was investigate teamwork and communication among event management personnel, to assess the degree to which PROBE, the advanced prototype they were using to manage a CBRNE simulation, would adequately meet their needs. The study was a continuation of previous research conducted in the early phase of PROBE development. Two communication-related analyses were applied to identify instances of effective and of ineffective communication among the management team. These revealed that communication was mostly effective. However, the one serious communication breakdown that was observed could have had fatal consequences. It showed that great care must be taken to ensure the safety of first responders at all times when evaluating prototypes in the field. A list of questions was generated from the lessons learned to assist future researchers prepare for CBRNE field studies.