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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Olawunmi George, Rizwana Rizia, MD Fitrat Hossain, Nadiyah Johnson, Carla Echeveste, Jose Lizarraga Mazaba, et al. (2019). Visualizing Early Warning Signs of Behavioral Crisis in Military Veterans: Empowering Peer Decision Support. In Z. Franco, J. J. González, & J. H. Canós (Eds.), Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management. Valencia, Spain: Iscram.
Abstract: Several attempts have been made at creating mobile solutions for patients with mental disorders. A preemptive approach would definitely outdo a reactive one. This project seeks to ensure better crisis detection, by assigning patients (veterans) to caregivers (mentors). This is called the mentor-mentee approach. Enhanced with the use of mobile technology, veterans can stay connected in their daily lives to mentors, who have gone through the same traumatic experiences and have overcome them. A mobile application for communication between veterans and their mentors has been developed, which helps mentors get constant feedback from their mentees about their state of well-being. However, being able to make good deductions from the data given as feedback is of great importance. Under-represent ing or over-representing the data could be dangerously misleading. This paper presents the design process in this project and the key things to note when designing a data visualization for
timely crisis detection and decision-making.
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Stijn Oomes. (2004). Organization awareness in crisis management: Dynamic organigrams for more effective disaster response. In B. C. B. Van de Walle (Ed.), Proceedings of ISCRAM 2004 – 1st International Workshop on Information Systems for Crisis Response and Management (pp. 63–68). Brussels: Royal Flemish Academy of Belgium.
Abstract: Disaster response organizations are ad-hoc assemblies of multiple emergency services that collaborate with the goal to minimize the number of casualties and possible (infra)structural damage. In order to be effective, emergency personnel not only needs shared awareness of the situation but also awareness of the organization. We propose an organization awareness support system that contains a dynamic organigram that provides people with a real-time visualization of the organization that they belong to. © Proceedings ISCRAM 2004.
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Ramsey, A., Kale, A., Kassa, Y., Gandhi, R., & Ricks, B. (2023). Toward Interactive Visualizations for Explaining Machine Learning Models. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 837–852). Omaha, USA: University of Nebraska at Omaha.
Abstract: Researchers and end users generally demand more trust and transparency from Machine learning (ML) models due to the complexity of their learned rule spaces. The field of eXplainable Artificial Intelligence (XAI) seeks to rectify this problem by developing methods of explaining ML models and the attributes used in making inferences. In the area of structural health monitoring of bridges, machine learning can offer insight into the relation between a bridge’s conditions and its environment over time. In this paper, we describe three visualization techniques that explain decision tree (DT) ML models that identify which features of a bridge make it more likely to receive repairs. Each of these visualizations enable interpretation, exploration, and clarification of complex DT models. We outline the development of these visualizations, along with their validity by experts in AI and in bridge design and engineering. This work has inherent benefits in the field of XAI as a direction for future research and as a tool for interactive visual explanation of ML models.
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Wolfgang Raskob, Florian Gering, & Valentin Bertsch. (2009). Approaches to visualisation of uncertainties to decision makers in an operational decision support system. 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: Decision making in case of any emergency is associated with uncertainty of input data, model data and changing preferences in the decision making process. Uncertainty handling was from the beginning an integral part of the decision support system RODOS for the off-site emergency management following nuclear or radiological emergencies. What is missing so far is the visualisation of the uncertainties in the results of the model calculations. In this paper we present the first attempt to visualise uncertain information in the early and late phase of the decision making process. For the early phase, the area of sheltering was selected as example. For the later phase, the results of the evaluation subsystem of RODOS were selected being used for the analysis of remediation measures such as agricultural management options. Both attempts are still under discussion but the presentation of the early phase uncertainty will be realised in the next version.
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Anthony C. Robinson, Alexander Savelyev, Scott Pezanowski, & Alan M. MacEachren. (2013). Understanding the utility of geospatial information in social media. 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. 918–922). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: Crisis situations generate tens of millions of social media reports, many of which contain references to geographic features and locations. Contemporary systems are now capable of mining and visualizing these location references in social media reports, but we have yet to develop a deep understanding of what end-users will expect to do with this information when attempting to achieve situational awareness. To explore this problem, we have conducted a utility and usability analysis of SensePlace2, a geovisual analytics tool designed to explore geospatial information found in Tweets. Eight users completed a task analysis and survey study using SensePlace2. Our findings reveal user expectations and key paths for solving usability and utility issues to inform the design of future visual analytics systems that incorporate geographic information from social media.
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Marco Romano, Teresa Onorati, Paloma Díaz, & Ignacio Aedo. (2014). Improving emergency response: Citizens performing actions. 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. 170–174). University Park, PA: The Pennsylvania State University.
Abstract: The role of common citizens within the emergency management (EM) process is crucial in order to support efficiently the operators' activities during the response phase. Moreover, their participation is strictly related to their profile and their experience in previous events. In a previous contribution we identified the different roles that the citizens can play for an effective cooperation with the EM workers. In this paper, we introduce an emergency tool based on a mobile application designed to support the activities of the citizens acting as Agent. The Agents have specific capabilities recognized by the EM Operation Center (OC) to execute actions under the remote supervision of the EM operators. The proposed tool allows the Agents to receive information from the OC and to visualize it through an advanced visualization modality. In particular, available information is previously collected by the center from the witnesses and the affected people that have alerted about it.
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Ryan K. Williams, Nicole Abaid, James McClure, Nathan Lau, Larkin Heintzman, Amanda Hashimoto, et al. (2020). Collaborative Multi-Robot Multi-Human Teams in Search and Rescue. In Amanda Hughes, Fiona McNeill, & Christopher W. Zobel (Eds.), ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management (pp. 973–983). Blacksburg, VA (USA): Virginia Tech.
Abstract: Robots such as unmanned aerial vehicles (UAVs) deployed for search and rescue (SAR) can explore areas where human searchers cannot easily go and gather information on scales that can transform SAR strategy. Multi-UAV teams therefore have the potential to transform SAR by augmenting the capabilities of human teams and providing information that would otherwise be inaccessible. Our research aims to develop new theory and technologies for field deploying autonomous UAVs and managing multi-UAV teams working in concert with multi-human teams for SAR. Specifically, in this paper we summarize our work in progress towards these goals, including: (1) a multi-UAV search path planner that adapts to human behavior; (2) an in-field distributed computing prototype that supports multi-UAV computation and communication; (3) behavioral modeling that yields spatially localized predictions of lost person location; and (4) an interface between human searchers and UAVs that facilitates human-UAV interaction over a wide range of autonomy.
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André Sabino, Rui Nóbrega, Armanda Rodrigues, & Nuno Correia. (2008). Life-saver: Flood emergency simulator. In B. V. de W. F. Fiedrich (Ed.), Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management (pp. 724–733). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: This paper proposes an agent-based simulation system for Dam Break Emergency Plan validation. The proposed system shows that integrating GIS data with an agent-based approach provides a successful simulation platform for the emergency plan validation process. Possible strategies to emergency plan modeling and representation are discussed, proposing a close relation with the actual workflow followed by the entities responsible for the plan's specification. The simulation model is mainly concerned with the location-based and location-motivated actions of the involved agents, describing the likely effects of a specific emergency situation response. The simulator architecture is further described, based on the correspondence between the representation of the plan, and the simulation model. This includes the involving characteristics of the simulation, the simulation engine, the description of the resulting data (for the later evaluation of the emergency plan) and a visualization and interaction component, enabling the dynamic introduction of changes in the scenario progression.
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Seungwon Yang, Haeyong Chung, Xiao Lin, Sunshin Lee, Liangzhe Chen, Andrew Wood, et al. (2013). PhaseVis1: What, when, where, and who in visualizing the four phases of emergency management through the lens of social media. 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. 912–917). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: The Four Phase Model of Emergency Management has been widely used in developing emergency/disaster response plans. However, the model has received criticism contrasting the clear phase distinctions in the model with the complex and overlapping nature of phases indicated by empirical evidence. To investigate how phases actually occur, we designed PhaseVis based on visualization principles, and applied it to Hurricane Isaac tweet data. We trained three classification algorithms using the four phases as categories. The 10-fold cross-validation showed that Multi-class SVM performed the best in Precision (0.8) and Naïve Bayes Multinomial performed the best in F-1 score (0.782). The tweet volume in each category was visualized as a ThemeRiver[TM], which shows the 'What' aspect. Other aspects – 'When', 'Where', and 'Who' – Are also integrated. The classification evaluation and a sample use case indicate that PhaseVis has potential utility in disasters, aiding those investigating a large disaster tweet dataset.
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Sterl, S., Billig, A., Taffo, F. W., & Gerhold, L. (2023). Visualizing the Psychosocial Situation in Crises and Disasters: Conceptualizing a Multi-Functional Crisis Information Platform (CIP-PS). In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 252–262). Omaha, USA: University of Nebraska at Omaha.
Abstract: Crises and disasters are becoming more frequent, long-lasting, complex, and interdependent. This can lead to negative psychosocial consequences in vulnerable population groups, increasing the need to (1) monitor psychosocial indicators and (2) make information on psychosocial topics available to decision-makers, the scientific community, and the public. In this WiPe paper, we present a way to systematically visualize, research, and document different types of psychosocial data in crises and disasters by developing a “Multi-Functional Crisis Information Platform for Psychosocial Situations”, called CIP-PS. The CIP-PS has three components, i.e., an information dashboard (CIP-DAB), a research platform (CIP-REP), and a documentation (CIP-DOC) component which together help visualize, research and document psychosocial topics, such as the psychosocial situation picture in Germany. The platform is a valuable tool for presenting relevant psychosocial information in the context of disaster public health. Its strength lies in an extensive connection between the three components related to healthcare informatics.
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Mark F. Taylor, & Russell J. Graves. (2005). Adaptive risk-readiness decision support for infrastructure protection. In B. C. B. Van de Walle (Ed.), Proceedings of ISCRAM 2005 – 2nd International Conference on Information Systems for Crisis Response and Management (pp. 161–169). Brussels: Royal Flemish Academy of Belgium.
Abstract: This paper presents a system concept for integrating the mass of information critical to infrastructure protection operations. Our main focus and contribution lies in (1) coupling risk assessments into a dynamic decision support process, and (2) providing a collaboration and visualization decision support interface for representing complex and changing infrastructure protection information. The system concept supports adaptive decision making based upon dynamic risk and readiness assessments. Users benefit from having a more comprehensive and up-to-date risk picture on which to base their judgments.
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Brian M. Tomaszewski, & Lóránt Czárán. (2009). Geographically visualizing consolidated appeal process (CAP) information. 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: Maps are essential visual advocacy devices for humanitarian relief projects. Maps provide advocacy by presenting, disseminating, and analyzing humanitarian relief project information in formats that are easier to understand and reason with. In this paper, we present our preliminary work on geographically visualizing Consolidated Appeals Process (CAP) information. The practical intent of our work is to (a) provide advocacy for CAP projects by geographically representing project information such as funding status so that (b) the nature of a project is better understood, thus potentially leading to increased project donations and improved project funding decision making. We provide examples of a prototype mapping application built to utilize Google Earth[TM] for representing CAP project information in map-based formats.
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Brian M. Tomaszewski, & Alan M. MacEachren. (2006). A distributed spatiotemporal cognition approach to visualization in support of coordinated group activity. In M. T. B. Van de Walle (Ed.), Proceedings of ISCRAM 2006 – 3rd International Conference on Information Systems for Crisis Response and Management (pp. 347–351). Newark, NJ: Royal Flemish Academy of Belgium.
Abstract: Technological advances in both distributed cooperative work and web-map services have the potential to support distributed and collaborative time-critical decision-making for crisis response. We address this potential through the theoretical perspective of distributed cognition and apply this perspective to development of a geocollaborationenabled web application that supports coordinated crisis management activities. An underlying goal of our overall research program is to understand how distributed cognition operates across groups working to develop both awareness of the geographic situation within which events unfold, and insights about the processes that have lead to that geographic situation over time. In this paper, we present our preliminary research on a web application that addresses these issues. Specifically, the application (key parts of which are implemented) enables online, asynchronous, map-based interaction between actors, thus supporting distributed spatial and temporal cognition, and, more specifically, situational awareness and subsequent action in the context of humanitarian disaster relief efforts.
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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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Chris J. Van Aart, & Stijn Oomes. (2008). Real-time organigraphs for collaboration awareness. In B. V. de W. F. Fiedrich (Ed.), Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management (pp. 651–659). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Collaboration awareness, as extension to organization awareness, is knowing how organizations do work and achieve their goals. This knowledge moves on a scale from stated prescribed ways of acting (such as procedures and protocols) to informal channels of communication, teamwork and decision-making. Based on available static and dynamic data, standardized insights can be given about collaboration in emergency situations in the form of organigraphs. We argue that for gaining practical collaboration awareness, both the formal structure of an organization as well as informal interactions should be inspected. Informal interaction includes informal communication channels, actual decision making on the spot and multi-disciplinary joint activities. We have implemented our system in the form of a web-based visualization tool. This tool would have been useful in the Hercules disaster, giving insights in informal information exchange, possibly preventing fatal decisions.
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Vimala Nunavath, Jaziar Radianti, Tina Comes, & Andreas Prinz. (2015). Visualization of Information Flows and Exchanged Information: Evidence from an indoor fire game. In L. Palen, M. Buscher, T. Comes, & A. Hughes (Eds.), ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management. Kristiansand, Norway: University of Agder (UiA).
Abstract: Understanding information flows is essential to improve coordination information systems. Aims of such systems are typically reducing information overload and improving situational awareness. Yet, there is a lack of intuitive and easily understandable tools that help to structure and visualize the ad hoc information flows that occur during search and rescue operations. In this paper, we present the concept of such an analysis, and present findings from an indoor serious fire game. For this game, we describe the interactions of Emergency Responders (ER), including individual information (over-)load, and descriptions of content of communications. This approach therefore provides an effective way to learn about active teams, information flows, exchanged information, and overload.
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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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Christopher W. Zobel. (2010). Comparative visualization of predicted disaster resilience. 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: The disaster resilience triangle is a simple but effective tool for illustrating the relationship between the initial impact of a disaster event and the subsequent time to recovery. This tool can also be expanded, however, to provide an analytic measure of the level of resilience exhibited by a particular entity in a given disaster situation. We build upon the previous work in this area by developing a new approach for visualizing and analyzing the tradeoffs between the two primary defining characteristics of the disaster resilience triangle. This new approach supports strategic decision making in a disaster planning environment by providing a straightforward means for directly comparing the relative predicted resilience of different critical facilities within an organization, with respect to both location and type of risk.
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Christopher W. Zobel. (2011). Representing the multi-dimensional nature of disaster resilience. 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: Although quantitative analytical information systems are an important resource for supporting decision-making in disaster operations management, not all aspects of a disaster situation can be easily quantified. For example, although the concept of the disaster resilience of a community has a technical dimension within which one can measure the resistance of the infrastructure against, and the speed of its recovery from, a disaster event, it also has social, organizational, and economic dimensions within which these characteristics may be more difficult to measure. This work-in-progress paper introduces a quantitative framework within which the multi-dimensional nature of such disaster resilience can be represented in a concise manner. This can help to improve understanding of the complexities associated with the concept, and thus directly support decision-making in disaster operations planning and management.
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