Kaisa Riikka Ylinen, & Juha Pekka Kilpinen. (2018). Calibrating Ensemble Forecasts to Produce More Reliable Probabilistic Extreme Weather Forecasts. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 1089–1097). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: Accurate predictions of severe weather events are extremely important for society, economy, and environment. Due to the fact that weather forecasts are inherently uncertain, it is required to give information about forecast uncertainty to all users providing weather forecasts in probabilistic terms utilizing ensemble forecasts. Since ensemble forecasts tend to be under dispersive and biased, they need to be calibrated with statistical methods. This paper presents a method for the calibration of temperature forecasts using Gaussian regression, and the calibration of wind gust forecasts with a box-cox t-distribution method. Statistical calibration was made for the operational European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble prediction system (ENS) forecasts for lead times from 3 to 360 hours. The verification results showed that calibration improved both temperature and wind gust ensemble forecasts. The probabilistic temperature forecasts were better after calibration over whole lead time scale, but the probabilistic wind gust forecasts up to 240 hours.
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Belinda Braunstein, Troy Trimble, Rajesh Mishra, B.S. Manoj, Leslie Lenert, & Ramesh R. Rao. (2006). Challenges in using of distributed wireless mesh networks in emergency response. In M. T. B. Van de Walle (Ed.), Proceedings of ISCRAM 2006 – 3rd International Conference on Information Systems for Crisis Response and Management (pp. 30–38). Newark, NJ: Royal Flemish Academy of Belgium.
Abstract: Wireless Mesh Networks (WMNs) are formed by self-organized wireless nodes that use multi-hop wireless relaying. These networks are useable in a variety of situations ranging from fixed residential broadband networking based on rooftop wireless mesh nodes to emergency response networks for handling large scale disasters. Quick deployability, minimal configuration, broadband communication, and easiness of reconfigurability are the major characteristics that make WMNs a suitable choice for emergency applications. There exist several open research issues in using such WMNs for emergency response applications. We, in this paper, present a hybrid distributed wireless networking architecture, Extreme Networking System (ENS), and present large set of performance observations collected from a real distributed hybrid wireless mesh network used for supporting a medical emergency response application. We present the traffic behavior observed in our network when a client server medical emergency response application is employed. The performance observations on real-traffic scenarios for emergency response application underlines the need for focusing further research on topology control, reliability, service availability, and distributed management. We observed that though there are several challenges that need to be solved, a WMN is a favorable choice for emergency response networking.
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S.H.M. Fakhruddin. (2006). Community based cost effective early warning dissemination network (EWDN). In M. T. B. Van de Walle (Ed.), Proceedings of ISCRAM 2006 – 3rd International Conference on Information Systems for Crisis Response and Management (pp. 50–51). Newark, NJ: Royal Flemish Academy of Belgium.
Abstract: Natural disasters are frequent in Bengladesh. Because Bengladesh has a fragile economy that is mostly dependent on agriculture, these events can be disastrous to the economy and people of the country. Adequate warnings to the community and institutions can mitigate the deleterious effects. This paper presents a model for an effective disaster warning and dissemination system (EWDN) that can provide timely and accurate alerts of natural disasters thus reducing loss of life, property and other risks.
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Thomas Usländer, & Ingo Simonis. (2015). Geospatial ICT Support for Crisis Management and Response. 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: Efficient crisis response and management requires well-informed actors and stakeholders and effective means for communication and policy enforcement. A secure and dependable geospatial information and communication technology (ICT) infrastructure may be an indispensable aid if it is tailored to the needs of the respective risk and crisis management phases and the various users.
During an ISCRAM 2015 workshop experts of the risk and crisis management community meet software architects and engineers of the geospatial domain. The objective is to investigate use cases and map them to capabilities of an underlying geospatial ICT infrastructure. The workshop shall launch a sustainable discussion between ISCRAM and the Open Geospatial Consortium (OGC), especially its Emergency and Disaster Management (EDM) domain working group, beyond ISCRAM 2015.
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Yaniv Mordecai, & Boris Kantsepolsky. (2018). Intelligent Utilization of Dashboards in Emergency Management. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 1108–1119). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: Effective decision-supporting visualization is critical for strategic, tactic, and operational management before and during a large-scale climate or extreme weather emergency. Most emergency management applications traditionally consist of map-based event and object visualization and management, which is necessary for operations, but has small contribution to decision makers. At the same time, analytical models and simulations that usually enable prediction and situation evaluation are often analyst-oriented and detached from the operational command and control system. Nevertheless, emergencies tend to generate unpredictable effects, which may require new decision-support tools in real-time, based on alternative data sources or data streams. In this paper, we advocate the use of dashboards for emergency management, but more importantly, we propose an intelligent mechanism to support effective and efficient utilization of data and information for decision-making via flexible deployment and visualization of data streams and metric displays. We employ this framework in the H2020 beAWARE project that aims to develop and demonstrate an innovative framework for enhanced decision support and management services in extreme weather climate events.
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Shelly Farnham, Elin R. Pedersen, & Robert Kirkpatrick. (2006). Observation of katrina/rita groove deployment: Addressing social and communication challenges of ephemeral groups. In M. T. B. Van de Walle (Ed.), Proceedings of ISCRAM 2006 – 3rd International Conference on Information Systems for Crisis Response and Management (pp. 39–49). Newark, NJ: Royal Flemish Academy of Belgium.
Abstract: In order to better understand the challenges specific to the deployment of collaboration technologies in crisis situations, we conducted an informal observational study of the deployment of Groove Virtual Office to various civil and military groups at the heart of the disaster zone over the course of ten days. We summarize both general lessons learned from observations of social and communication challenges in crisis situations that impact technology adoption, and make specific recommendations for improving the deployment process of Groove to enable cross group collaboration. We generally found that dynamic, informal social networks and lightweight ephemeral work groups were essential social structures in the relief effort, and we discuss the need to innovate technologies to support these alternative types of organizations. We encourage that current technology centric innovation for ephemeral workgroups is complemented by a usage centric approach to help address emergent behaviors and opportunities.
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Federico Angaramo, & Claudio Rossi. (2018). Online clustering and classification for real-time event detection in Twitter. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 1098–1107). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: Event detection from social media is a challenging task due to the volume, the velocity and the variety of user-generated data requiring real-time processing. Despite recent works on this subject, a generalized and scalable approach that could be applied across languages and topics has not been consolidated, yet. In this paper, we propose a methodology for real-time event detection from Twitter data that allows users to select a topic of interest by defining a simple set of keywords and a matching rule. We implement the proposed methodology and evaluate it with real data to detect different types of events.
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Efstratios Kontopoulos, Panagiotis Mitzias, Jürgen Moßgraber, Philipp Hertweck, Hylke van der Schaaf, Désirée Hilbring, et al. (2018). Ontology-based Representation of Crisis Management Procedures for Climate Events. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 1064–1073). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: One of the most critical challenges faced by authorities during the management of a climate-related crisis is the overwhelming flow of heterogeneous information coming from humans and deployed sensors (e.g. cameras, temperature measurements, etc.), which has to be processed in order to filter meaningful items and provide crisis decision support. Towards addressing this challenge, ontologies can provide a semantically unified representation of the domain, along with superior capabilities in querying and information retrieval. Nevertheless, the recently proposed ontologies only cover subsets of the relevant concepts. This paper proposes a more “all-around” lightweight ontology for climate crisis management, which greatly facilitates decision support and merges several pertinent aspects: representation of a crisis, climate parameters that may cause climate crises, sensor analysis, crisis incidents and related impacts, first responder unit allocations. The ontology could constitute the backbone of the decision support systems for crisis management.
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Alessandro Farasin, & Paolo Garza. (2018). PERCEIVE: Precipitation Data Characterization by means on Frequent Spatio-Temporal Sequences. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 1081–1088). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: Nowadays large amounts of climatology data, including daily precipitation data, are collected by means of sensors located in different locations of the world. The data driven analysis of these large data sets by means of scalable machine learning and data mining techniques allows extracting interesting knowledge from data, inferring interesting patterns and correlations among sets of spatio-temporal events and characterizing them. In this paper, we describe the PERCEIVE framework. PERCEIVE is a data-driven framework based on frequent spatio-temporal sequences and aims at extracting frequent correlations among spatio-temporal precipitation events. It is implemented by using R and Apache Spark, for scalability reasons, and provides also a visualization module that can be used to intuitively show the extracted patterns. A preliminary set of experiments show the efficiency and the effectiveness of PERCEIVE.
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Iftikhar Ali, Vahid Freeman, Senmao Cao, & Wolfgang Wagner. (2018). Sentinel-1 Based Near-Real Time Flood Mapping Service. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 1074–1080). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: Globally floods are categorized as one of most devastating natural disasters and annually causing a major loss to human lives and economy. For rapid damage assessment and planning relief activities a large scale spatio-temporal overview is required to assist local authorities. This paper aims to provide an overview of a Sentinel-1 based near-real time flood mapping/monitoring service; which is implemented as an operational service under the framework of I-REACT (Improving Resilience to Emergencies through Advanced Cyber Technologies) project.
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Katrina Petersen, & Monika Büscher. (2015). Technology in Disaster Response and Management: Narratives of Ethical, Legal, and Social Issues. 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: Ethical, legal and social issues (ELSI) are widely recognised as important in IT innovation for crisis response and management. However, attention often struggles to get beyond theorising basic concepts, when the realities of how difficulties and opportunities manifest are complex and practical. Unless these realities are understood, solutions to ELSI will remain at the surface, missing opportunities to responsibly and creatively leverage the potential of IT in disaster response. This workshop brings together narratives of lived experiences of ethical, legal, and social issues encountered in the context of IT innovation in disaster response, and analyses of normative, policy and regulatory backgrounds. In this editorial, we motivate this turn to narrative, summarise the contributions that will be presented on the day, and set out some key questions.
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Eva Blomqvist, Vitaveska Lanfranchi, Suvodeep Mazumdar, Tomi Kauppinen, & Carsten Kessler. (2015). Workshop summary: Workshop on Semantics and Analytics for Emergency Response (SAFE2015). 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: The Emergency Response domain is a highly challenging domain, requiring the active collaboration of several experts and authorities on the one hand and large-scale data analysis on the other. This poses significant challenges in sharing and analysing highly dynamic data describing highly evolving situations. This paper provides a brief summary for the first workshop in the SAFE workshop series. The workshop is aimed at bringing together analysts, practitioners, researchers and enthusiasts and provides a discussion ground for practical problems, solutions and projects that exploit Semantic Web, Linked Data analytics for Emergency Response. Following a round of thorough reviews, four papers are accepted and a keynote will complement the paper presentations along with a few discussion sessions.
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