Ooms, D. (2023). Civil-Military Interaction: a Case Study to validate a Conceptual Framework. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 501–515). Omaha, USA: University of Nebraska at Omaha.
Abstract: International peace operations in response to complex emergencies require effective interaction between international civil and military participants and local actors. Although these operations frequently occur worldwide, civil-military interaction (CMI) remains problematic. CMI problems are described in the literature at length. However, the knowledge management aspects of these problems have received less attention. The feasibility of technical support solutions for CMI should be investigated using a design science approach. This requires validated models of the structural and behavioral characteristics of the CMI domain. A CMI conceptual framework providing such models has been proposed earlier and should be validated. A case study has been conducted into a Netherlands military CMI organization. This study provides for initial user validation of the models. In follow-on research, the validated conceptual framework is used to structure the investigation of CMI problems, knowledge process deficiencies, and their causal relations. It may subsequently support knowledge engineering-based solution design.
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Kiran Zahra, Rahul Deb Das, Frank O. Ostermann, & Ross S. Purves. (2022). Towards an Automated Information Extraction Model from Twitter Threads during Disasters. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 637–653). Tarbes, France.
Abstract: Social media plays a vital role as a communication source during large-scale disasters. The unstructured and informal nature of such short individual posts makes it difficult to extract useful information, often due to a lack of additional context. The potential of social media threads– sequences of posts– has not been explored as a source of adding context and more information to the initiating post. In this research, we explored Twitter threads as an information source and developed an information extraction model capable of extracting relevant information from threads posted during disasters. We used a crowdsourcing platform to determine whether a thread adds more information to the initial tweet and defined disaster-related information present in these threads into six themes– event reporting, location, time, intensity, casualty and damage reports, and help calls. For these themes, we created the respective thematic lexicons from WordNet. Moreover, we developed and compared four information extraction models trained on GloVe, word2vec, bag-of-words, and thematic bag-of-words to extract and summarize the most critical information from the threads. Our results reveal that 70 percent of all threads add information to the initiating post for various disaster-related themes. Furthermore, the thematic bag-of-words information extraction model outperforms the other algorithms and models for preserving the highest number of disaster-related themes.
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Julian Zobel, Patrick Lieser, Tobias Meuser, Lars Baumgärtner, Mira Mezini, & Ralf Steinmetz. (2021). Modeling Civilian Mobility in Large-Scale Disasters. In Anouck Adrot, Rob Grace, Kathleen Moore, & Christopher W. Zobel (Eds.), ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management (pp. 119–132). Blacksburg, VA (USA): Virginia Tech.
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.
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Hans Christian Augustijn Wienen, Faiza Allah Bukhsh, Eelco Vriezekolk, & Roel J. Wieringa. (2018). Accident Analysis Methods and Models – a Systematic Review. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 398–408). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: After a risk has manifested itself and has led to an accident, valuable lessons can be learned that can be taken into account to reduce the risk of a similar accident occurring again. This calls for accident analysis methods. In the past 20 years a large number of accident analysis methods have been proposed and it is difficult to find the right method to apply in a specific circumstance. We conducted a review of the state of the art of accident analysis methods and models across domains. We classify the models using the well-known categorization into sequential, epidemiological and systemic methods. We find that these classes have their own characteristics in terms of speed of application versus pay-off. For optimum risk reduction, methods that take organizational issues into account can add valuable information to the risk management process in an organization.
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Xiaodan Yu, & Deepak Khazanchi. (2017). Studying Virtual Teams during Organizational Crisis from a Sociomaterial Perspective. In eds Aurélie Montarnal Matthieu Lauras Chihab Hanachi F. B. Tina Comes (Ed.), Proceedings of the 14th International Conference on Information Systems for Crisis Response And Management (1055). Albi, France: Iscram.
Abstract: In this paper, we propose sociomaterialism as a theoretical lens for studying virtual team management during organizational crisis. In applying this lens, we propose the use of pattern theory as the method of choice for documenting effective practices for managing virtual teams in organizational crisis settings.
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