Abstract: Early Warning Systems (EWS) provide an effective measure for better disaster preparedness, response, and mitigation. The effectiveness of EWS depends highly on the ability to distribute alert message to the persons that will be affected. In this context mobile devices play already a vital role in the ability to reach people in time and at the endangered location. Most existing approaches focus on mass dissemination methods via SMS and Cell-Broadcasting. As these approaches are effective to inform masses about a disaster with one message for all they have their weaknesses in telling the people how to respond according to their location and provide individual guidance (e.g. by maps) within specific communities. Research in disaster management gives strong evidence that the later is often crucial for better disaster response. Accordingly, we witness an increasing demand for more community-centered warnings systems solutions. This paper introduces the general foundations and architecture for alert services on mobile devices that adapt incoming alert information to the profile and situation of user groups and even individual users. The approach is scalable for different communitycentered warning systems. Its first applicability and community engagement effects are shown in the example of the community-centered public disaster alert system in Germany and a target group specific weather hazard alert system, KATWARN and WIND with currently over 2.5 million subscribed users, which was developed by the authors.

Abstract: Decision support systems can recommend strategies for disaster management, which can be further discussed by decision-makers. To provide rationales for the recommendations, the strategies need to be assessed according to relevant criteria. If several strategies are available, the criteria can be used for ranking the strategies. This paper addresses the issue concerning the choice of suitable criteria from several perspectives. The assessment integrates concepts on robustness, experience with regard to the implementation of a strategy, quantifiable ratios which can be deduced from simulations, and system-specific parameters. Objectives are to facilitate transparency with respect to the assessments, to provide a basis for discussions concerning the strategies, and to preserve adaptability and flexibility to account for the variability of disasters and users' preferences. The assessment should be used for ranking solutions gained from a case-based reasoning system and to reveal contributions of criteria values to the overall assessment.

Abstract: Assessing a system's vulnerability is a widely used method to estimate the effects of risks. In the past years, increasingly dynamic vulnerability assessments were developed to display changes in vulnerability over time (e.g. in climate change, coastal vulnerability, and flood management). This implies that the dynamic influences of management strategies on vulnerability need to be considered in the selection and implementation of strategies. For this purpose, we present a strategy evaluation framework which is based on dynamic vulnerability assessments. The key contribution reported in this paper is an evaluation framework that considers how well strategies achieve a predefined target level of protection over time. Protection Target Levels are predefined objectives. The framework proposed is inspired by Goal Programming methods and allows distinguishing the relevance of time-dependent achievements by weights. This enables decision-makers to evaluate the overall performance of strategies, to test strategies, and to compare the outcome of strategies.

Abstract: In the response to emergencies and disasters, effective cooperation and information exchange between military and civil actors is essential. However, in practice, the quality of civil-military interaction (CMI) leaves much to be desired. Our research takes an engineering approach, which is complementary to most behavioral-oriented research in the CMI domain. In particular, we seek to support CMI processes with innovative Information Technology solutions. To this end, we are developing a comprehensive conceptual model of the CMI domain, which is currently lacking. This paper contributes to its development by investigating candidate technologies and defining CMI domain model requirements. Exploiting these requirements as criteria, we have evaluated three modeling methods and languages, i.e. the Unified Modeling Language (UML), the Business Process Modeling Notation (BPMN) and the Design and Engineering Methodology for Organizations (DEMO). Based on the comparative study, we conclude that a combination of these is required for modeling the CMI domain.

Abstract: This paper advances a growing body of mobile mapping work which captures building scale tornado damage in order to reveal vulnerabilities, or protections, within an otherwise apparently homogenous damage path. The hope is to find how micro geography, or built environment structure patterning might lead to policy advances with regards to rebuilding of critical infrastructure in tornado prone areas. This paper will use spatially encoded video to record damage patterns for the Washington, Illinois tornado of November 17, 2013. What makes this event notable is the location and time of year which can be considered outside the norm. Individual building damage data are coded using the Tornado Injury Scale (TIS) and then analyzed using two forms of local area spatial analysis – a Getis-Ord (Gi) z-score analysis to identify hotspots of damage, and a Local Moran's I to identify building outliers within hotspots.

Abstract: During crises directly affected people and observers join social media communities to discuss the event. They may share information relevant to response coordination, for example, specific resource needs. However, responders face a massive data overload and lack the time to monitor social media traffic for important and trustworthy information. To address these challenges, response teams may attempt manual filtering methods, resulting in limited coverage and quality. Hence, we propose a computational framework for extracting specific resource-related information, and an interface for identifying and engaging with influential participants in the dynamic, evolving social media community. Our approach helps to identify those virtual responders who serve both as sources and disseminators of important information to assist in coordinated emergency response.

Abstract: Emergency situations are unavoidable. This paper presents the functions inherent in a prototype system that was developed in Malaysia for emergency management. The prototype is potentially useful in Selangor, a state in Malaysia that is prone to natural disasters such as flash floods and landslides. The paper is presented as a report of our on-going project in Malaysia and the intended future work regarding web-based emergency management systems in Malaysia. This prototype development is funded by the Ministry of Education in Malaysia and supported by the National Security Council of Malaysia (Majilis Keselamatan Negara, MKN).

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.

Abstract: In the situation of mass casualty incidents in Germany the questions that always remain are what and how much resources are needed to provide the best response. Furthermore, there are many local-specific constraints that exist, such as the density of hospitals nearby, what their surgery capacities are like, the distance between the local rescue bases and the incident scene as well as the level of preparedness of first responders. This paper describes an organisational approach to elaborate the specific tactical strategies that take part in preparedness planning. Furthermore, this paper will give insight and explore a simulation information system to support local medical response managers in elaborating those strategies in an office environment.

Abstract: The identification of elements at risk is an essential part in hazard risk assessment. Especially for recurring natural hazards like floods, an updated database with information about elements exposed to such hazards is fundamental to support crisis preparedness and response activities. However, acquiring and maintaining an up-to-date database with elements at risk requires both detailed local and hazard-specific knowledge, being often a challenge for local communities and risk management bodies. We present a new approach for leveraging Volunteered Geographic Information to identify elements at risk from the free and open-source mapping project OpenStreetMap. We present initial results from a case study in the city of Cologne, Germany, to validate our approach in the case of flood-hazard. Our results show that the identification of elements at flood risk from OpenStreetMap is a suitable and cost-effective alternative for supporting local governments and communities in risk assessment and emergency planning.

Abstract: Previous research claimed that organizational stress, due to task complexity and time pressure, leads to considerably negative effects on the decision-making performance of individuals and organizations. At the same time, intellectual capital (IC), in providing intangible internal and external organizational assets has a positive effect on organizational decision-making performance. This paper develops a structural equation model to analyze the relationships among IC, task complexity, time pressure and decision-making performance. Empirical data are collected from 374 participants, who are from universities, institutes, enterprises, government, with different occupations and expertise. We present two conclusions. First, IC consisting of internal capital, human capital and external capital leads to a reduced complexity of tasks and reduced time pressure and hence reduced organizational stress. Second, reduced organizational stress results in higher levels of performance for organizational decision-making.

Abstract: Analysis of social media and traditional media provides significant information to first responders in times of natural disasters. Sentiment analysis, particularly of social media originating from the affected population, forms an integral part of multifaceted media analysis. The current paper extends an existing methodology to the domain of natural disasters, broadens the support of multiple languages and introduces a new manner of classification. The performance of the approach is evaluated on a recently collected dataset manually annotated by three human annotators as a reference. The experiments show a high agreement rate between the approach taken and the annotators. Furthermore, the paper presents the initial application of the resulting technology and models to sentiment analysis of social media data in German, covering data collected during the Central European floods of 2013.