Abstract: The communications of emergency response managers were tracked during simulated catastrophic events at a university campus in the Washington, D.C. region. Local, state, and federal response managers interacted with each other and with students using a variety of communication media in order to investigate the utility of new communication channels for emergency response management. Students and emergency managers interacted using a Twitter-like platform and a portal built with Ushahidi crowd-sourcing software. The emergency managers also used a chat interface that included private instant messaging, telephone, and the county's existing emergency web portal. Their media use was analyzed along with the functions of their communications, and the patterns that emerged are described and quantified.

Abstract: Today emergencies seem more complex than ever. Process of managing these emergencies also becomes more complex because of increasing number of involved parties, increasing number of people affected, and increasing amount of resources. This complexity, inherent in emergency management, brings lots of challenges to decision makers and emergency responders. Information systems and technologies are utilized in different areas of emergency management. However complexity increases exponentially in emergency situations and it requires more sophisticated IS and IT and it makes response and management more challenging. Thus analyzing the root causes of emergency management information systems complexity is crucial for improving emergency response effectiveness. This paper frames the issue of information systems complexity by focusing on the types of complexities involved in emergency management phases and explaining each complexity type. We propose 6 different complexity types: Human Complexity, Technologic Complexity, Event Complexity, Interaction Complexity, Decision Making Complexity, and Cultural Complexity.

Abstract: The OASIS Project addresses the Strategic objective 2.3.2.9, “Improving Risk Management”, of the second call for tender of the European Commission FP6 Information Society Technologies program. The objective of OASIS is to define and develop an Information Technology (IT) framework based on an open and flexible architecture and using standards that will be the basis of a European Emergency Management system. OASIS is intended to facilitate the cooperation between the information systems used by civil protection organisations, in a local, regional, national or international environment. This Disaster and Emergency Management system aims to support the response operations in the case of large scale as well as local emergencies.

Abstract: Disaster risk management practitioners have the responsibility to make decisions at every phase of the disaster risk management cycle: mitigation, preparedness, response and recovery. The decisions they make affect human life. In this paper, we consider the current state of the use of AI in information extraction (IE) for disaster risk management (DRM), which makes it possible to leverage disaster information in social media. We consolidate the challenges and concerns of using AI for DRM into three main areas: limitations of DRM data, limitations of AI modeling and DRM domain-specific concerns, i.e., bias, privacy and security, transparency and accountability, and hype and inflated expectations. Then, we present a systematic discussion of how explainable AI (XAI) can address the challenges and concerns of using AI for IE in DRM.

Abstract: Taxonomies are integral to systems engineering, as they structure our knowledge of a field and so provide the
foundation for technological development. We contribute such taxonomies for the field of Community
Interaction and Engagement in Crisis and Disaster Management, which represents the interface between
members of the public who commit to relief efforts and established organisations that have a pre-defined role in
crisis management. These actors are unified in their purpose to help those in need, but also set apart by their
organisational structures and modes of operation. We classify the actors of Community Interaction and
Engagement, as well as the interactions between them. Our contribution outlines areas where the application of
Information and Communication Technology can offer benefits to Community Interaction and Engagement.

Abstract: Spontaneous volunteers influence crisis and disaster relief efforts as both an effective aid and a stressing factor for emergency organisations. Managing the negative impacts of spontaneous volunteering has thus become part of command and control deliberations. In this paper, we take a closer look at integrating spontaneous volunteers into the formal response system to mitigate negative impacts.
Working with participants from formal response organisations, we gathered qualitative data regarding the management of spontaneous volunteers during the European migration crisis in 2015.
Through thematic analysis, we extracted topics to systematically describe the interaction between emergency organisations and spontaneous volunteers. As implication thereof, we propose how computer supported systems can be applied to better manage spontaneous volunteers. In our discussion, we focus on the registration process and ad hoc verification of spontaneous volunteers to better integrate them in the formal response process.

Abstract: Online social media has been recognized as a valuable information source for disaster management whose volume, velocity and variety exceed manual processing capacity. Current machine learning systems that support the processing of such data generally follow a human-in-the-loop approach, which has several inherent limitations. This work applies the human-is-the-loop concept from visual analytics to semi-automate a manual content moderation workflow, wherein human moderators take the dominant role. The workflow is instantiated with a supervised machine learning system that supports moderators with suggestions regarding the relevance and categorization of content. The instantiated workflow has been evaluated using in-depth interviews with practitioners and serious games. which suggest that it offers good compatibility with work practices in humanitarian assessment as well as improved moderation quality and higher flexibility than common approaches.

Abstract: The extensive use of social media platforms, especially during disasters, creates unique opportunities for humanitarian organizations to gain situational awareness and launch relief operations accordingly. In addition to the textual content, people post overwhelming amounts of imagery data on social networks within minutes of a disaster hit. Studies point to the importance of this online imagery content for emergency response. Despite recent advances in the computer vision field, automatic processing of the crisis-related social media imagery data remains a challenging task. It is because a majority of which consists of redundant and irrelevant content. In this paper, we present an image processing pipeline that comprises de-duplication and relevancy filtering mechanisms to collect and filter social media image content in real-time during a crisis event. Results obtained from extensive experiments on real-world crisis datasets demonstrate the significance of the proposed pipeline for optimal utilization of both human and machine computing resources.

Abstract: This paper presents the results of our research on the development of a Dialog Action Manager-DAM as part of a complex crisis management system. Imagine the utility of such an automatic system to detect the crisis and to provide support to people in contexts similar to what happened recently at the underground in London and Madrid. Preventing and handling the scenarios of terrorism and other crisis are nowadays maybe the most important issues for a modern and safe society. In order to automate the crisis support, DAM simulates the behavior of an employee at the crisis centre handling telephone calls from human observers. Firstly, the system has to mimic the natural support for the paradigm 'do you hear me?' and next for the paradigm 'do you understand me?'. The people witnessing the crisis event as well as human experts provide reports and expertise according to their observations and knowledge on the crisis. The system knowledge and the data communication follow the XML format specifications. The system is centered on the results of our previous work on creating a user-centered multimodal reporting tool that works on mobile devices. In our paper we describe the mechanisms for creating an automatic DAM system that is able to analyze the user messages, to identify and track the crisis contexts, to support dialogs for crisis information disambiguation and to generate feedback in the form of advice to the users. The reasoning is done by using a data frame and rule based system architecture and an alternative Bayesian Network approach. In the paper we also present a series of experiments we have attempted in our endeavor to correctly identify natural solutions for the crisis situations.

Abstract: The Global Disaster Alert and Coordination System, jointly developed by the European Commission and the United Nations, combines existing web-based disaster information management systems with the aim to alert the international community in case of major sudden-onset disasters and to facilitate the coordination of international response during the relief phase of the disaster. The disaster alerts are based on automatic hazard information retrieval and real-time running of impact models. This paper describes impact models for earthquakes, tsunamis and tropical cyclones.

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.

Abstract: In crisis situations different organizations have to cooperate to gain shared situation awareness and to take accurate decisions. However, several evaluation studies of crisis mitigation processes indicate that it is hard to effectively coordinate efforts of all organizations involved. The goal of our project is to improve coordination in crisis management teams, by improving the interaction processes in a crisis management team. The project consists of two main steps. First, the development of MIRROR, i.e. an overview of 16 relevant factors that influence team interaction. Second, the development of a training based on MIRROR. We expect MIRROR and its training module to be a useful tool for team members of crisis teams. In addition, MIRROR has the advantage that it can be applied in non-crisis teams, during daily situations, as well. This enlarges the chances for potential team members of crisis teams to increase their team interactions skills. © 2012 ISCRAM.