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Werner Leyh, Maria Clara Fava, Narumi Abe, Camilo Restrepo Estrada, Flavio Horita, Eduardo Mario Mendiondo, et al. (2016). SDI-Node to interlink Information, essential for Disaster Preparedness and Management, with other Linked Open Data. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
Abstract: The idea on Linked Open Data (LOD) for Disaster Management was stimulated by the experience with the integration of heterogeneous environmental data based on well-known OGC based web services. A lot of spatial data is available 'via the Web' – but not ?really on the web': many datasets can be viewed, queried and downloaded via web services, but it is usually not possible to reference an entity within a dataset, like a web page. However, persistent identifiers and deep and reliable linking between datasets and tools are frequently required, beyond file level, to items ?within? files. This becomes possible using Semantic Web (SW) technologies, such as the ?Resource Description Framework? (RDF), and opens possibilities to integrate or aggregate subsets of datasets based on logical criteria. Ontological modelling is used to represent conceptual knowledge. This SW approach is able to handle SPARQL queries considering property relations and ontological models. Disaster related data is multidisciplinary by nature, and comprises data entities from observations, experiments, surveys, simulations, models, and higher-order assemblies, along with associated metadata. The present work with AGORA´s SDI-NODE focuses on connecting dispersed disaster-relevant data to enable easier and faster discovery and access of disaster-related data. The cloud-based geographical information system is hereby explored in 3 ways: Firstly it serves as a reference implementation for the current state of art in SDI; Secondly it serves as praxis relevant use case for disaster relevant data and information management: it is worldwide developed and earlier versions are already used by many countries for their national disaster preparedness – with regard to its ability in rapid and easy mapping and its flexibility to be quickly adapted to unpredictable and fast changing crisis scenarios, and thirdly because it serves already, “partially”, as a SDI-LOD-bridge: The SDI node is composed by underlying components (like GeoServer, GeoNode and GeoNetWork) and some of the supporting communities are already developing different facilities to promote the desired SDI+LOD integration. Thus, the ?LOD-enabled SDI-node? explores LOD related technologies to query, integrate and aggregate, over distributed datasets, at feature-level. Final example: The LOD-enabled SDI-Node is a highly appropriate approach and solution to integrate, track, map, catalog and serve information on the ZIKA VIRUS, the AEDES MOSQUITOES and their environmental conditions.
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Xia Wu, & Yi Xiong. (2016). Computer-based scheme-making system of emergency maintenance for failure of oil and gas pipeline. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
Abstract: Accident of oil and gas pipeline may result in enormous economic loss, great casualties and severe environmental pollution (Assael and Kakosimos, 2010). In the field of pipeline accident emergency, the Decision Support System (DSS) has been proposed to reduce the loss of an accident (Dey, 2001; Agbenowosi, 2000; Nataraj, 2005). However, their researches are mostly about risk management (Dey, 2001), materials scheduling (Agbenowosi, 2000), theory (Nataraj, 2005) and process of response, which are served for the decision-makers. In fact, though one of the most important steps of emergency response for accident of oil and gas pipeline is maintenance implemented, there is no enough attention paid on the maintenance scheme-making.
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Yang Gao. (2016). Risk Zoning of the Urban Shelter in Earthquake. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
Abstract: In order to deal with the huge threat and loss caused by the earthquake, established the evaluation system and model, and the risk zoning map is drawn according to the study of the vulnerability of Xicheng District's streets. According to the spatial coupling relationship between social vulnerability and physical vulnerability, drawn the comprehensive risk zoning map of Shichahai street as a typical case. The results show that Xicheng District and Shichahai street have their own vulnerability, which is very different from the social vulnerability and physical vulnerability of different streets and communities.
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Yasir Javed. (2016). Sensors-based Crisis Response and Management for Mass Gatherings: A Case of Hajj. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
Abstract: Many people die or are lost every year during mass gatherings around the world hence making it very difficult for the local authorities to track them and identify them in case of accidents. This paper proposes a system for tracing of lost, injured and dead using network of Radio Frequency Identifiers (RFID) tags and mobile phones. With such a system, time, effort, and cost can be significantly minimized hence eliminating the psychological torture through which relatives of the lost passes though. The proposed system can also be used for crowd management in a real time. For outdoor tracking, where placing RFID readers is not practical, the paper proposes mobile-based peer to peer network for tracking pilgrims who don?t have access to the internet or don?t have GPS facility in their mobile phones. The paper also proposed a plan of testing the prototype in simulation.
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Yi Xiong, Weiping Si, & Xia Wu. (2016). Analysis of Emergency Response for Accident of Oil and Gas Pipeline Based on Stochastic Petri Net. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
Abstract: Emergency response plays an important role in reducing the loss of an accident. And the excellent plan is important to ensure the high efficiency of the emergency response system. However, actions of emergency response arranged in emergency plan can hardly be assessed before the plan is used. Stochastic Petri Net (SPN) is proposed to analyze the performance of emergency response for oil and gas pipeline accident. The results show that the average execution time of SPN model can be used to evaluate effectiveness of emergency response. Then place average mark number indicates that emergency decision-making is the most important segment to optimize emergency work flow. And utilization rate of transition shows that decreasing the cost time of maintenance is the key to improve efficiency of emergency response.
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Yiting Zheng, Jianguo Chen, Wenjie Tang, & Jiaxiang Xu. (2016). Research on Target Diversity and Risk Analysis Model of Terrorist Attack. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
Abstract: Terrorist attack continues to spread in the world which leads to severe casualties and property losses and poses great pressure to the government. Therefore it is essential to identify the potential targets terrorists may select, assess the risk level and take risk management measures in advance. Aiming to this problem, the paper provides a new analysis method. Firstly it investigates target types terrorists prefer to and target diversity based on the data in Global Terrorist Database ; Then it puts forward the target risk analysis of three-dimensional model which considers the threat probabilityã?the target vulnerability and the consequence severity; Finally, the paper calculates and assesses the risk level using the fuzzy synthesis decision-making method, and two examples are given to prove the feasibility of the model. The result can contribute to target risk analysis and emergency preparedness or management of terrorist attack.
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Yuhong Li, & Christopher Zobel. (2016). Small Businesses and Social Media Usage in the 2013 Colorado Floods. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
Abstract: The recovery of small businesses from a disaster is critical to community recovery. Such businesses can be extremely vulnerable to disasters, particularly because they often occupy a single location and have a localized customer base. Although social media is an effective platform for information dissemination, and has been extensively used in a disaster context, the way in which small businesses use social media in this context, and the effectiveness of those efforts, are still not well understood. With this in mind, this paper uses the 2013 floods along the Front Range in Colorado as a case study to help improve our understanding of how small businesses use social media in disaster situations. Characterizing the organizations' behavior involves using both qualitative and quantitative approaches, and the paper focuses on an initial qualitative analysis.
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Zeno Franco, Katinka Hooyer, Rizwana Rizia, A B M Kowser Patwary, Mathew Armstrong, Bryan Semaan, et al. (2016). Dryhootch Quick Reaction Force: Collaborative Information Design to Prevent Crisis in Military Veterans. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
Abstract: Crises range from global catastrophes to personal disasters. However, systematic inquiry on crises rarely employs a comparative approach to examine commonalities between these seemingly very different events. We argue here that individual psychosocial disasters can inform a broader discussion on crises. Our approach applies general crisis theory to a smartphone based psychosocial support system for US military veterans. We engaged in a process designed to explore how veteran peer-to-peer mentorship can be augmented with IS support to display potential early warning signs as first step toward preventative intervention for high risk behaviors. To gain a better understanding of how military veterans might benefit from such a system, this article focuses on a community collaborative design process. The co-design process used the Small Stories method, allowing important cultural characteristics of to emerge, illuminating considerations in IS design with military veterans, and highlighting how humans think about crisis events at the individual level.
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Zoltán Balogh, Emil Gatial, & Ladislav Hluchý. (2016). Poll Sourcing for Crisis Response. In A. Tapia, P. Antunes, V.A. Bañuls, K. Moore, & J. Porto (Eds.), ISCRAM 2016 Conference Proceedings ? 13th International Conference on Information Systems for Crisis Response and Management. Rio de Janeiro, Brasil: Federal University of Rio de Janeiro.
Abstract: During large scale crisis response operations there is an acute and continuous need to efficiently and quickly allocate a dynamically changing supply of resources. In this paper we are proposing a system, which uses polls to seamlessly discover, request, collect and aggregate information from engaged resource providers using the web or mobile devices. At the same time we aim to integrate information from sources such as sensors deployed on incident sites, publicly available open data, corporate legacy systems or documents stored on remote locations. The overall process of such Poll Sourcing also encompasses reservation and order of suitable resources. We provide a validation scenario concerning reservation of hospital beds during a mass casualty incident.
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