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	Author	Marion Lara Tan; Sara Harrison; Julia S. Becker; Emma E.H. Doyle; Raj Prasanna
	Title	Research Themes on Warnings in Information Systems Crisis Management Literature			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	1085-1099
	Keywords	Early Warnings Systems, Literature Review, Ethics, Social Media.
	Abstract	Early Warning Systems (EWS) are crucial to mitigating and reducing disaster impacts. Furthermore, technology and information systems (IS) are key to the success of EWSs. This systematic literature review investigates the research topics and themes from the past six years of Information Systems for Crisis Response and Management (ISCRAM) conference proceedings and seeks to identify the research developments and directions for EWSs to steer a discourse to advance the research in this field. Findings from a sample size of 60 papers show that there are technical, social, and topical considerations to using and advancing technology for EWSs. While technology has advanced EWSs to new levels, it is important to consider the influence of technology in the successful operation of EWSs. The results are based on the ISCRAM proceedings literature and may be broader or have different prioritization if a wider disciplinary body of literature was explored. This will be considered in the future.
	Address	Massey University; Massey University; Massey University; Massey University; Massey University
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-98	ISBN	2411-3484	Medium
	Track	Visions for Future Crisis Management	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	M.L.Tan@massey.ac.nz			Approved	no
	Call Number				Serial	2299
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	Author	Aurélie Congès; Alexis Evain; Olivier Chabiron; Col. Jacob Graham(USMC, R.); Frédérick Benaben
	Title	Virtual Reality to Train for Crisis Management			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	1100-1112
	Keywords	Virtual reality; Crisis Management; Exercises; Decision-Support System
	Abstract	The EGCERSIS project aims at using virtual reality to improve the efficiency of the crisis management preparation phase. The idea is to tackle the drawbacks of regular crisis management exercises thanks to fully configurable scenarios taking place in digital twins of real critical sites. Virtual exercises will improve, among other things, the frequency, efficiency, and modularity of crisis management preparation, while reducing its costs. In this article, we demonstrate the idea of the project through a simple use-case taking place in a metro station and involving three crisis responders. By linking virtual exercises to our crisis management platform, we also want to demonstrate the usefulness of decision-support systems during a crisis.
	Address	IMT Mines Albi; IMT Mines Albi; Immersive Factory; The Pennsylvania State University; IMT Mines Albi
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-99	ISBN	2411-3485	Medium
	Track	Visions for Future Crisis Management	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	aurelie.conges@mines-albi.fr			Approved	no
	Call Number				Serial	2300
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	Author	Hanne Haaland; Hege Wallevik; Erika Frydenlund; Jose J. Padilla
	Title	Modelers and Ethnographers as Co-Creators of Knowledge: Do We Belong Together?			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	1113-1121
	Keywords	Social Sciences; Modeling; Interdisciplinarity; Citizen-Based Humanitarian Aid; Refugees; Lesvos; Citizen Initiatives for Global Solidarity (CIGS); Prototype Agent-Based Model
	Abstract	In this paper, we explore the process of co-creation of knowledge between modelers and ethnographers through a project focusing on the role played by CIGS (Citizen initiatives for global solidarity) in the refugee crisis in the island of Lesvos, Greece. We describe the process of collaboration and discuss what this type of interdisciplinary collaboration may bring to the development of a research topic when the initial skepticism and questions of epistemological differences have been overcome. Moreover, we address some of the challenges embedded in this type of research collaboration, particularly the skepticism present within the social sciences.
	Address	University of Agder, Norway; University of Agder, Norway; Old Dominion University, US; Old Dominion University, US
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-100	ISBN	2411-3486	Medium
	Track	Visions for Future Crisis Management	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	Hanne.haaland@uia.no			Approved	no
	Call Number				Serial	2301
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	Author	Anne-Marie Barthe-Delanoë; Wenxin Mu
	Title	Towards a Context-Aware Systemic Risk Management Framework for the Crisis Response			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	1122-1129
	Keywords	Context-Awareness; Risk Analysis; Risk Evaluation; Knowledge Base; Systemic Risk
	Abstract	Crisis response is, as any other collaborative networked organization, challenged by changes and vulnerabilities. Moreover, as a complex system with distributed activities and numerous interdependencies, considering the risk of such an organization at a systemic level, including time and space dimensions, is necessary. Systemic risk management is a topic traditionally studied in the finance area. Even if a few researches now focus on the supply chain management area (a more relatable domain regarding crisis response), there is even fewer literature regarding systemic risk management for the crisis response. Thus, this paper proposes first to define systemic risk related to the case of the crisis response. Then, a framework for context-aware systemic risk management is presented, to support the design as well as the follow-up of the crisis response, meeting one of the challenges of the Sendai Framework for Disaster Risk Reduction.
	Address	Laboratoire de Génie Chimique, Université de Toulouse, CNRS, INPT, UPS, Toulouse, France; Department of Information Management, Jiao Tong University, Beijing, China
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-101	ISBN	2411-3487	Medium
	Track	Visions for Future Crisis Management	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	annemarie.barthe@ensiacet.fr			Approved	no
	Call Number				Serial	2302
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	Author	Frederick Benaben; Lysiane Benaben
	Title	Science Fiction: Past and Future Trends of Crisis Management			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	1130-1139
	Keywords	Information; Decision; Action; Future; Trends; Anticipation; Framework
	Abstract	This paper is a position paper, presenting an original but very anticipative and mainly imaginative vision of the evolution of the crisis management domain. After analyzing the options to make the past evolutions of that domain somehow explainable (mainly by analyzing the data of all the articles of the last fifteen editions of the ISCRAM conference), the paper aims at providing a framework to assess and evaluate the maturity of the domain of crisis management. Moreover, this framework is also used to tentatively infer some future evolutions and some directions that could be relevant, dangerous, tricky or of great benefit for the crisis management domain. These future trends are mainly based on the current maturity of crisis management (according to the proposed framework) and current or future influential practices, technologies or threats. It will be necessary to wait for fifteen years to see if these bets should be considered as accurate.
	Address	IMT Mines Albi; IMT Mines Albi
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-102	ISBN	2411-3488	Medium
	Track	Visions for Future Crisis Management	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	frederick.benaben@mines-albi.fr			Approved	no
	Call Number				Serial	2303
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	Author	Deena Disraelly; Laura Itle
	Title	Providing Reliable Assistance Faster: Secure, Modern, Mission-Capable Credentialing to Support Disaster Operations			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	1140-1143
	Keywords	Credentialing; Disaster Support; Clearance; Suitability; Volunteer
	Abstract	The public sector, including state and local government, public health, and emergency management; the private sector; and the Federal Government jointly face challenges with rapidly collecting and validating credentials for individuals applying for employment or volunteering for emergencies, vetting security clearances, and ascertaining suitability. In 2017, for instance, credentialing gaps delayed employees and volunteers from contributing much-needed skills in disaster areas during one of the worst hurricane and wildfire seasons on record while Federal agencies inadvertently issued interim clearances to individuals with criminal records. We propose a secure, modern, mission-capable information technology solution to these with the United States Postal Service hosting this streamlined process by serving as the hub for collection, validation, and transfer of pertinent data. The solution would introduce access points in over 5,000 communities for citizens participating in disaster support operations, as well as those requiring credentialing for employment as part of day-to-day operations.
	Address	Institute for Defence Analysis, Virginia USA; Institute for Defence Analysis, Virginia USA
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-103	ISBN	2411-3489	Medium
	Track	Visions for Future Crisis Management	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	ddisrael@ida.org			Approved	no
	Call Number				Serial	2304
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	Author	Daniel Lichte; Dustin Witte; Kai-Dietrich Wolf
	Title	Comprehensive Security Hazard Analysis for Transmission Systems			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	1145-1153
	Keywords	Physical Security; Energy Transmission Systems; Scenario Analysis; Threat Analysis; Risk Assessment
	Abstract	Critical energy infrastructures are more and more focused upon by politics and society. Modern society depends on these structures, since they enable the steady support of electricity and other types of energy. Deliberately precipitated hazards of certain critical parts of electrical transmission systems (ETS) can lead to catastrophic consequences. Therefore, the analysis of feasible security hazards and resulting consequences for the operation of transmission systems are a concern to transmission system operators (TSO). Alas, there is no common method available that comprehensively identifies these feasible security related scenarios and classifies them according to their overall criticality for the safe operation of the ETS. To tackle this challenge, we propose a comprehensive, yet easy-to-apply method to systematically identify and assess the criticality of security threat scenarios. It is conducted in four steps and consists of a matrix based consistency check of threat scenarios in a defined solution space and a convenient semi-quantitative assessment of a risk factor for the ETS. The approach is illustrated by the simplified generic example of an EETS.
	Address	German Aerospace Center; University of Wuppertal; University of Wuppertal
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-104	ISBN	2411-3490	Medium
	Track	Open Track	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	daniel.lichte@dlr.de			Approved	no
	Call Number				Serial	2305
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	Author	Cecilia Hammar Wijkmark; Ilona Heldal
	Title	Virtual and Live Simulation-Based Training for Incident Commanders			Type	Conference Article
	Year	2020	Publication	ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2020
	Volume		Issue		Pages	1154-1162
	Keywords	Virtual Simulation; Simulation; Serious Games; Training; Live Training; Cost and Benefit; Use; Usability; Incident Command
	Abstract	Computer and virtual simulation-based training (CST) offer several benefits for emergency response and management preparedness. However, organizations responsible for training are often hesitant to use CST, based on cost and perceived lack of benefit when compared to live simulation training (LST). This paper investigates how CST can complement LST, and how it contributes to achieving the necessary learning objectives for level one fire and rescue service incident commanders (ICs). Data and examples come from an experimental study with students from different fire and rescue services trained in the role of the IC in LST and CST, in a similar scenario. Results show the cost and benefits of the CST implementation based on evaluations from learners, instructors and responsible managers. Participants had a positive attitude towards using virtual simulations, but the results also point to barriers regarding the suitable design of learning scenarios and implementation.
	Address	Western Norway University of Applied Sciences; Western Norway University of Applied Sciences
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Amanda Hughes; Fiona McNeill; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-27-105	ISBN	2411-3491	Medium
	Track	Open Track	Expedition		Conference	17th International Conference on Information Systems for Crisis Response and Management
	Notes	Cecilia.hammar.wijkmark@hvl.no			Approved	no
	Call Number				Serial	2306
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	Author	Xiaojing Guo; Xinzhi Wang; Luyao Kou; Hui Zhang
	Title	A Question Answering System Applied to Disasters			Type	Conference Article
	Year	2021	Publication	ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2021
	Volume		Issue		Pages	2-16
	Keywords	Emergency Management, Disaster, Natural Language Processing, Deep Learning
	Abstract	In emergency management, identifying disaster information accurately and promptly out of numerous documents like news articles, announcements, and reports is important for decision makers to accomplish their mission efficiently. This paper studies the application of the question answering system which can automatically locate answers in the documents by natural language processing to improve the efficiency and accuracy of disaster knowledge extraction. Firstly, an improved question answering model was constructed based on the advantages of the existing neural network models. Secondly, the English question answering dataset pertinent to disasters and the Chinese question answering dataset were constructed. Finally, the improved neural network model was trained on the datasets and tested by calculating the F1 and EM scores which indicated that a higher question answering accuracy was achieved. The improved system has a deeper understanding of the semantic information and can be used to construct the disaster knowledge graph.
	Address	Institute of Public Safety Research, Tsinghua University; School of Computer Engineering and Science, Shanghai University; Institute of Public Safety Research, Tsinghua University; Institute of Public Safety Research, Tsinghua University
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-61-5	ISBN		Medium
	Track	AI and Intelligent Systems for Crises and Risks	Expedition		Conference	18th International Conference on Information Systems for Crisis Response and Management
	Notes	gxj19@mails.tsinghua.edu.cn			Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2308
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	Author	Nada Matta; Thomas Godard; Guillaume Delatour; Ludovic Blay; Franck Pouzet; Audrey Senator
	Title	Analyzing Social Media in Crisis Management Using Expertise Feedback Modelling			Type	Conference Article
	Year	2021	Publication	ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2021
	Volume		Issue		Pages	17-27
	Keywords	Social Media analysis, TextMining, sentiment analysis, crisis management, decision making
	Abstract	Currently social media are largely used in interactions, especially in crisis situations. We note a big volume of interactions around events. Observing these interactions give information even to alert the existence of an incident, event, or to understand the expansion of a problem. Crisis management actors observe social media to be aware about this type of information in order to consider them in their decisions. Specific organizations are founded in order to observe social media interactions and send their analysis to rescue and crisis management actors. In our work, an experience feedback of this type of organizations (VISOV, a crisis social media analysis association) is capitalized in order to emphasize from one side, main dimensions of this analysis and from another side, to simulate some aspects using TextMining that help to explore big volume of data.
	Address	University of Technology of Troyes; University of Technology of Troyes; University of Technology of Troyes; VISOV; CS Group; ENSOSP
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-61-5	ISBN		Medium
	Track	AI and Intelligent Systems for Crises and Risks	Expedition		Conference	18th International Conference on Information Systems for Crisis Response and Management
	Notes	nada.matta@utt.fr			Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2309
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	Author	Audun Stolpe; Jo Hannay
	Title	On the Adaptive Delegation and Sequencing of Actions			Type	Conference Article
	Year	2021	Publication	ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2021
	Volume		Issue		Pages	28-39
	Keywords	Decision support, AI Planning, Delegation, Sequencing, Adaptivity, Cognitive processes
	Abstract	Information systems support to crisis response and management relies crucially on presenting actionable information in a manner that supports cognitive processes, and does not overwhelm them. We outline how AI Planning can be used viably to support the \emph{delegation and sequencing} of tasks. The idea is to use standard operating procedures as initial specifications of plans in terms of actors, actions and delegation rules. When expressed in the AI planning language \textit{Answer set Programming} (ASP), machine reasoning can be used in a \textit{pre-incident review} to display relevant delegation and sequencing inherent in a plan. % together with measures of goal achievement. The purpose of this is to uncover weaknesses in the initial plan and to optimize sequencing and delegation to increase the likelihood of achieving goals. Further, adaptive planning can be supported in \textit{during-incident reviews} by updating the current status, upon which ASP will then compute new alternatives. % and corresponding goal achievement measures. At this point, initial goals may no longer be viable and the explicit suggestion of prior sub-optimal goals now worth pursuing can be a game-changer under stress. The conceptual basis we lay out in terms of delegation and sequencing can be readily extended with further planning factors, such as resource requirements, role transfer and goal achievement.
	Address	Norwegian Computing Center; Norwegian Computing Center
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-61-5	ISBN		Medium
	Track	AI and Intelligent Systems for Crises and Risks	Expedition		Conference	18th International Conference on Information Systems for Crisis Response and Management
	Notes	audun.stolpe@its.uio.no			Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2310
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	Author	Nilani Algiriyage; Raj Prasanna; Kristin Stock; Emma Hudson-Doyle; David Johnston; Minura Punchihewa; Santhoopa Jayawardhana
	Title	Towards Real-time Traffic Flow Estimation using YOLO and SORT from Surveillance Video Footage			Type	Conference Article
	Year	2021	Publication	ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2021
	Volume		Issue		Pages	40-48
	Keywords	Computer Vision, Traffic Flow, YOLOv4, CCTV Big Data
	Abstract	Traffic emergencies and resulting delays cause a significant impact on the economy and society. Traffic flow estimation is one of the early steps in urban planning and managing traffic infrastructure. Traditionally, traffic flow rates were commonly measured using underground inductive loops, pneumatic road tubes, and temporary manual counts. However, these approaches can not be used in large areas due to high costs, road surface degradation and implementation difficulties. Recent advancement of computer vision techniques in combination with freely available closed-circuit television (CCTV) datasets has provided opportunities for vehicle detection and classification. This study addresses the problem of estimating traffic flow using low-quality video data from a surveillance camera. Therefore, we have trained the novel YOLOv4 algorithm for five object classes (car, truck, van, bike, and bus). Also, we introduce an algorithm to count the vehicles using the SORT tracker based on movement direction such as ``northbound'' and ``southbound'' to obtain the traffic flow rates. The experimental results, for a CCTV footage in Christchurch, New Zealand shows the effectiveness of the proposed approach. In future research, we expect to train on large and more diverse datasets that cover various weather and lighting conditions.
	Address	Massey University; Massey University; Massey University; Joint Centre for Disaster Research, Massey University; Joint Center of Disaster Research, Massey University Wellington; University of Kelaniya; Univerity of Kelaniya
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-61-5	ISBN		Medium
	Track	AI and Intelligent Systems for Crises and Risks	Expedition		Conference	18th International Conference on Information Systems for Crisis Response and Management
	Notes	rangika.nilani@gmail.com			Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2311
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	Author	Kenneth Johnson; Javier Cámara; Roopak Sinha; Samaneh Madanian; Dave Parry
	Title	Towards Self-Adaptive Disaster Management Systems			Type	Conference Article
	Year	2021	Publication	ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2021
	Volume		Issue		Pages	49-61
	Keywords	disaster management, self-adaptive systems, formal verification, probabilistic model checking, constraint solving
	Abstract	Disasters often occur without warning and despite extensive preparation, disaster managers must take action to respond to changes critical resource allocations to support existing health-care facilities and emergency triages. A key challenge is to devise sound and verifiable resourcing plans within an evolving disaster scenario. Our main contribution is the development of a conceptual self-adaptive system featuring a monitor-analyse-plan-execute (MAPE) feedback loop to continually adapt resourcing within the disaster-affected region in response to changing usage and requirements. We illustrate the system's use on a case study based on Auckland city (New Zealand). Uncertainty arising from partial knowledge of infrastructure conditions and outcomes of human participant's actions are modelled and automatically analysed using formal verification techniques. The analysis inform plans for routing resources to where they are needed in the region. Our approach is shown to readily support multiple model and verification techniques applicable to a range of disaster scenarios.
	Address	Auckland University of Technology; University of York; Auckland University of Technology; AUT university; Auckland University of Technology
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-61-5	ISBN		Medium
	Track	AI and Intelligent Systems for Crises and Risks	Expedition		Conference	18th International Conference on Information Systems for Crisis Response and Management
	Notes	kenneth.johnson@aut.ac.nz			Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2312
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	Author	Tina Mioch; Reinier Sterkenburg; Tatjana Beuker; Mark A. Neerincx
	Title	Actionable Situation Awareness: Supporting Team Decisions in Hazardous Situations			Type	Conference Article
	Year	2021	Publication	ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2021
	Volume		Issue		Pages	62-70
	Keywords	Situation Awareness, Actionability, Decision support, Chemical hazard
	Abstract	Situation Awareness (SA) has been recognized and studied as an important requirement for an effective task performance of first responders. The integration of increasingly advanced sensor, network and artificial intelligence technology into the work processes affects the building, maintenance and sharing of SA. Connecting SA to decision support models provides new possibilities for the development of actionable SA (aSA), entailing information that guides the momentary decision-making processes of the concerning actors. In the European ASSISTANCE project, we are developing an aSA module that displays information about gas distributions, its current and predicted future states (e.g., entailing risks of breathing-in of toxic gases), with references to effective decision-making patterns for this situation. The aSA model is continuously updated based on sensor data. This paper gives an overview of this aSA module for chemical hazard prediction and corresponding display, and presents initial team design patterns that will be integrated into this display to support its actionability.
	Address	Tno; Tno; Tno; Tno
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-61-5	ISBN		Medium
	Track	AI and Intelligent Systems for Crises and Risks	Expedition		Conference	18th International Conference on Information Systems for Crisis Response and Management
	Notes	tina.mioch@tno.nl			Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2313
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	Author	Oussema Ben Amara; Daouda Kamissoko; Frédérick Benaben; Ygal Fijalkow
	Title	Hardware architecture for the evaluation of BCP robustness indicators through massive data collection and interpretation			Type	Conference Article
	Year	2021	Publication	ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2021
	Volume		Issue		Pages	71-78
	Keywords	Business Continuity Plan, Social sciences, Risk Management, Robustness, Embedded Hardware
	Abstract	Recently, the concept of robustness measurement has become clearly important especially with the rise of risky events such as natural disasters and mortal pandemics. In this context, this paper proposes an overview of a hardware architecture for massive data collection in the aim of evaluating robustness indicators. This paper essentially addresses the theoretical and general problems that the scientific research is seeking to address in this area, offers a literature review of what already exists and, based on preliminary diagnosis of what the literature has, presents a new approach and some of the targeted findings with a focus on the leading aspects, having a primary objective of explaining the multiple aspects of this research work.
	Address	IMT Mines Albi, University of Toulouse; IMT Mines Albi, University of Toulouse; IMT Mines Albi, University of Toulouse; INU Champollion, University of Toulouse
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-61-5	ISBN		Medium
	Track	AI and Intelligent Systems for Crises and Risks	Expedition		Conference	18th International Conference on Information Systems for Crisis Response and Management
	Notes	oussema.ben_amara@mines-albi.fr			Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2314
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	Author	Antonio De Nicola; Maria Luisa Villani; Francesco Costantino; Andrea Falegnami; Riccardo Patriarca
	Title	Knowledge Fusion for Distributed Situational Awareness driven by the WAx Conceptual Framework			Type	Conference Article
	Year	2021	Publication	ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2021
	Volume		Issue		Pages	79-85
	Keywords	distributed situational awareness, knowledge fusion, WAx framework, crisis management, cyber-socio-technical systems
	Abstract	Large crisis scenarios involve several actors, acting at the blunt-end of the process, such as rescue team directors, and at the sharp-end, such as firefighters. All of them have different perspectives on the crisis situation, which could be either coherent, alternative or complementary. This heterogeneity of perceptions hinders situational awareness, which is defined as the achievement of an overall picture on the above-mentioned crisis situation. We define knowledge fusion as the process of integrating multiple knowledge entities to produce actionable knowledge, which is consistent, accurate, and useful for the purpose of the analysis. Hence, we present a conceptual modelling approach to gather and integrate knowledge related to large crisis scenarios from locally-distributed sources that can make it actionable. The approach builds on the WAx framework for cyber-socio-technical systems and aims at classifying and coping with the different knowledge entities generated by the involved operators. The conceptual outcomes of the approach are then discussed in terms of open research challenges for knowledge fusion in crisis scenarios.
	Address	ENEA; ENEA – CR Casaccia; Sapienza University of Rome; Sapienza University of Rome; Sapienza University of Rome
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-61-5	ISBN		Medium
	Track	AI and Intelligent Systems for Crises and Risks	Expedition		Conference	18th International Conference on Information Systems for Crisis Response and Management
	Notes	antonio.denicola@enea.it			Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2315
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	Author	Rouba Iskandar; Julie Dugdale; Elise Beck; Cécile Cornou
	Title	PEERS: An integrated agent-based framework for simulating pedestrians' earthquake evacuation			Type	Conference Article
	Year	2021	Publication	ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2021
	Volume		Issue		Pages	86-96
	Keywords	Seismic risk, human behavior, interdisciplinarity, evacuation, agent-based model
	Abstract	Traditional seismic risk assessment approaches focus on assessing the damages to the urban fabric and the resultant socio-economic consequences, without adequately incorporating the social component of risk. However, the human behavior is essential for anticipating the impacts of an earthquake, and should be included in quantitative risk assessment studies. This paper proposes an interdisciplinary agent-based modeling framework for simulating pedestrians' evacuation in an urban environment during and in the immediate aftermath of an earthquake. The model is applied to Beirut, Lebanon and integrates geo-spatial, socio-demographic, and quantitative behavioral data corresponding to the study area. Several scenarios are proposed to be explored using this model in order to identify the influence of relevant model parameters. These experiments could contribute to the development of improved of emergency management plans and prevention strategies.
	Address	Université Grenoble Alpes, ISTerre, Pacte, LIG; Université Grenoble Alpes, LIG; Université Grenoble Alpes, Pacte; Université Grenoble Alpes, ISTerre
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-61-5	ISBN		Medium
	Track	AI and Intelligent Systems for Crises and Risks	Expedition		Conference	18th International Conference on Information Systems for Crisis Response and Management
	Notes	rouba.iskandar@univ-grenoble-alpes.fr			Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2316
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	Author	Yasas Senarath; Jennifer Chan; Hemant Purohit; Ozlem Uzuner
	Title	Evaluating the Relevance of UMLS Knowledge Base for Public Health Informatics during Disasters			Type	Conference Article
	Year	2021	Publication	ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2021
	Volume		Issue		Pages	97-105
	Keywords	Public Health, Disaster Informatics, Health Informatics, UMLS, Metathesaurus
	Abstract	During disasters public health organizations increasingly face challenges in acquiring and transforming real-time data into knowledge about the dynamic public health needs. Resources on the internet can provide valuable information for extracting knowledge that can help improve decisions which will ultimately result in targeted and efficient health services. Digital content such as online articles, blogs, and social media are some of such information sources that could be leveraged to improve the health care systems during disasters. To efficiently and accurately identify relevant disaster health information, extraction tools require a common vocabulary that is aligned to the health domain so that the knowledge from these unstructured digital sources can be accurately structured and organized. In this paper, we study the degree to which the Unified Medical Language System (UMLS) contains relevant disaster, public health, and medical concepts for which public health information in disaster domain could be extracted from digital sources.
	Address	George Mason University; Northwestern University; George Mason University; George Mason University
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-61-5	ISBN		Medium
	Track	AI and Intelligent Systems for Crises and Risks	Expedition		Conference	18th International Conference on Information Systems for Crisis Response and Management
	Notes	ywijesu@gmu.edu			Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2317
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	Author	Dashley Rouwendal van Schijndel; Audun Stolpe; Jo Erskine Hannay
	Title	Toward an AI-based external scenario event controller for crisis response simulations			Type	Conference Article
	Year	2021	Publication	ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2021
	Volume		Issue		Pages	106-117
	Keywords	Scenario event controller, AI Planning, Modelling and Simulation, Simulation controller
	Abstract	There is a need for tool support for structured planning, execution and analysis of simulation-based training for crisisresponse and management. As a central component of an architecture for such tool support, we outline the design ofan AI-based scenario event controller. The event controller is a component that uses machine reasoning to computethe next state in a scenario, given the actions performed in the corresponding simulation (execution of the scenario).Scenarios are specified in Answer Set Programming, which is a logic programming language we use for automatedplanning of training scenarios. A plan encoding in ASP adds expressivity in scenario specification and enablesmachine reasoning. For exercise managers this gives AI-based tool support for before-action and during-actionreviews to optimize learning. In line with Modelling and Simulation as as Service, our approach externalizes eventcontrol from any particular simulation platform. The scenario, and its unfolding in terms of events, is externalizedas a service. This increases interoperability and enables scenarios to be designed and modified readily and rapidlyto adapt to new training requirements.
	Address	University of Oslo; Norsk Regnesentral; Norsk Regnesentral
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-61-5	ISBN		Medium
	Track	AI and Intelligent Systems for Crises and Risks	Expedition		Conference	18th International Conference on Information Systems for Crisis Response and Management
	Notes	d.k.rouwendal@its.uio.no			Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2318
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	Author	Julian Zobel; Patrick Lieser; Tobias Meuser; Lars Baumgärtner; Mira Mezini; Ralf Steinmetz
	Title	Modeling Civilian Mobility in Large-Scale Disasters			Type	Conference Article
	Year	2021	Publication	ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2021
	Volume		Issue		Pages	119-132
	Keywords	Civilian disaster communication, Delay-Tolerant Networks, Human mobility, Mobility models, Disaster response, Simulation
	Abstract	When disasters destroy critical communication infrastructure, smartphone-based Delay-Tolerant Networks (DTNs) can provide basic communication for civilians. Although field tests have shown the practicability of such systems, real-world experiments are expensive and hardly repeatable. Simulations are therefore required for the design and extensive evaluation of novel DTN protocols, but meaningful assertions require realistic mobility models for civilians. In this paper, trace files from a large-scale disaster field test are analyzed to identify typical human behavior patterns in a disaster area. Based on this, we derive a novel civilian disaster mobility model that incorporates identified behaviors such as group-based movement and clustering around points-of-interests such as hospitals and shelters. We evaluate the impact of mobility on DTN communication performance by comparing our model with other established mobility models as well as the trace file dataset in a simulative evaluation based on the field test scenario. In general, our mobility model leads to a more realistic assessment of DTN communication performance compared to other mobility models.
	Address	Technical University of Darmstadt; Technical University of Darmstadt; Technical University of Darmstadt; Technical University of Darmstadt; Technical University of Darmstadt; Technical University of Darmstadt
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-61-5	ISBN		Medium
	Track	Analytical Modeling and Simulation	Expedition		Conference	18th International Conference on Information Systems for Crisis Response and Management
	Notes	julian.zobel@kom.tu-darmstadt.de			Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2319
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	Author	Tobias Meuser; Lars Baumgärtner; Patrick Lieser
	Title	Pandemic Skylines: Digital Twins for More Realism in Epidemic Simulations			Type	Conference Article
	Year	2021	Publication	ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2021
	Volume		Issue		Pages	133-145
	Keywords	Simulation, Disaster Communication, Pandemic
	Abstract	In the recent months, many measures have been taken by governments to fight the COVID-19 pandemic. Due to the unknown properties of the disease and a lack of experience with handling pandemics, the effectiveness of measures taken was often hard to evaluate the effectiveness of measures, leading to inefficient measures and late execution of efficient measures. Many models have been proposed to evaluate the performance of these measures on the spreading of a pandemic, but these models are commonly vastly simplified and, thus, limited in expressiveness. To extend the expressiveness of the models, we developed a epidemic simulation inside of a flexible and scalable city simulation game to analyse the counter measures to a pandemic in this city and spot common places of infection on a microscopic level. The configurability of our developed epidemic simulation will also be useful for potential future pandemics.
	Address	TU Darmstadt – KOM; TU Darmstadt – STG; TU Darmstadt – KOM
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-61-5	ISBN		Medium
	Track	Analytical Modeling and Simulation	Expedition		Conference	18th International Conference on Information Systems for Crisis Response and Management
	Notes	tobias.meuser@kom.tu-darmstadt.de			Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2320
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	Author	Usman Anjum; Vladimir Zadorozhny; Prashant Krishnamurthy
	Title	TBAM: Towards An Agent-Based Model to Enrich Twitter Data			Type	Conference Article
	Year	2021	Publication	ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2021
	Volume		Issue		Pages	146-158
	Keywords	Agent-Based Model, Twitter, Modeling and Simulation, Event Detection
	Abstract	Twitter is widely being used by researchers to understand human behavior, e.g. how people behave when an event occurs and how it changes their microblogging pattern. The changing microblogging behavior can have an important application in the form of detecting events. However, the Twitter data that is available has limitations in it has incomplete and noisy information and has irregular samples. In this paper we create a model, calledTwitter Behavior Agent-Based Model (TBAM)to simulate Twitter pattern and behavior using Agent-Based Modeling(ABM). The generated data can be used in place or to complement the real-world data and improve the accuracy of event detection. We confirm the validity of our model by comparing it with real data collected from Twitter
	Address	University of Pittsburgh; University of Pittsburgh; University of Pittsburgh
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-61-5	ISBN		Medium
	Track	Analytical Modeling and Simulation	Expedition		Conference	18th International Conference on Information Systems for Crisis Response and Management
	Notes	usa3@pitt.edu			Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2321
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	Author	Xiaoyong Ni; Hong Huang; Wenxuan Dong; Chao Chen; Boni Su; Anying Chen
	Title	Scenario Prediction and Crisis Management for Rain-induced Waterlogging Based on High-precision Simulation			Type	Conference Article
	Year	2021	Publication	ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2021
	Volume		Issue		Pages	159-173
	Keywords	Rain-induced waterlogging, Scenario prediction, High-precision simulation, Crisis management
	Abstract	Many cities, especially those in developing countries, are not well prepared for the devastating disaster of exceptional rain-induced waterlogging caused by extreme rainfall. This paper proposes a waterlogging scenario prediction and crisis management method for such kind of extreme rainfall conditions based on high-precision waterlogging simulation. A typical urban region in Beijing, China is selected as the study area in this paper. High-precision and full-scale data in the study area requested for the waterlogging simulation are introduced. The simulation results show that the study area is still vulnerable to extreme rainfall and the subsequent waterlogging. The waterlogging situation is much more severe with the increase of the return period of rainfall. This study offers a good reference for the relevant government departments to make effective policy and take pointed response to the waterlogging problem.
	Address	Tsinghua University; Tsinghua University; Tsinghua University; Beijing Water Authority; Electric Power Planning & Engineering Institute; Tsinghua University
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-61-5	ISBN		Medium
	Track	Analytical Modeling and Simulation	Expedition		Conference	18th International Conference on Information Systems for Crisis Response and Management
	Notes	nxy15@mails.tsinghua.edu.cn			Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2322
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	Author	Alexander Gabriel; Babette Tecklenburg; Yann Guillouet; Frank Sill Torres
	Title	Threat analysis of offshore wind farms by Bayesian networks – a new modeling approach			Type	Conference Article
	Year	2021	Publication	ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2021
	Volume		Issue		Pages	174-185
	Keywords	Threat analysis, Bayesian networks, process modeling, Critical infrastructurs
	Abstract	As a result of the ongoing commitment to climate protection in more and more countries and the corresponding expansion of renewable energies, the importance of renewables for the security of electricity supply is also increasing. Wind energy generated in offshore wind farms already accounts for a significant share of the energy mix and will continue to grow in the future. Therefore, approaches and models for security assessment and protection against threats are also needed for these infrastructures. Due to the special characteristics and geographical location of offshore wind farms, they are confronted with particular challenges. In this context, this contribution outlines how an approach for threat analysis of offshore wind farms is to be developed within the framework of the new research project “ARROWS” of the German Aerospace Center. The authors first explain the structure of offshore wind farms and then present a possible modeling approach using Qualitative function models and Bayesian networks.
	Address	German Aerospace Center – Institute for the Protection of Maritime Infrastructures; German Aerospace Center – Institute for the Protection of Maritime Infrastructures; German Aerospace Center – Institute for the Protection of Maritime Infrastructures; Ger
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-61-5	ISBN		Medium
	Track	Analytical Modeling and Simulation	Expedition		Conference	18th International Conference on Information Systems for Crisis Response and Management
	Notes	Alexander.Gabriel@dlr.de			Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2323
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	Author	Ivar Svare Holand; Peter Mozelius; Trond Olav Skevik
	Title	A structured and dynamic model for emergency management exercises			Type	Conference Article
	Year	2021	Publication	ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management	Abbreviated Journal	Iscram 2021
	Volume		Issue		Pages	186-197
	Keywords	Emergency exercises, Vulnerability assessment, Non-linear emergency exercise model, Norwegian-Swedish cross-border collaboration, Gaining Security Symbiosis (GSS) projects
	Abstract	Emergencies are management challenges, and emergency exercises that involve multiple collaborating parties is a means towards mastering them. Such exercises are often conducted in a virtual training environment based on complex disaster scenarios. The reported study was carried out using a requirement-focused design approach. The aim was to describe and discuss a relevant design for lean, dynamic, and cost-efficient emergency management exercise systems. Data were gathered from a literature study and analyses of earlier emergency management projects in which the authors had participated. Despite the complexity of many current emergency management exercises, the scenarios usually involve only the response phases and have a linear structure that hinders both didactic aspects and the software structure. The conclusion drawn from the study is that an emergency management exercise model should focus on managing the activities that correspond to alternatives that unfold from a dynamic scenario. Finally, the authors recommend the principles of alternate reality games as a way towards more dynamic and cost-efficient emergency exercise systems.
	Address	Nord University; Mid Sweden University; Nord University
	Corporate Author				Thesis
	Publisher	Virginia Tech	Place of Publication	Blacksburg, VA (USA)	Editor	Anouck Adrot; Rob Grace; Kathleen Moore; Christopher W. Zobel
	Language	English	Summary Language	English	Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	978-1-949373-61-5	ISBN		Medium
	Track	Analytical Modeling and Simulation	Expedition		Conference	18th International Conference on Information Systems for Crisis Response and Management
	Notes	ivar.s.holand@nord.no			Approved	no
	Call Number	ISCRAM @ idladmin @			Serial	2324
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