Rustenberg, K., Radianti, J., & Gjøsæter, T. (2023). Exploring Demons for the Establishment of Team Situational Awareness. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 636–648). Omaha, USA: University of Nebraska at Omaha.
Abstract: Individual situational awareness (SA) is crucial for building team SA, which is necessary for achieving a shared understanding of a situation, making informed decisions, and taking appropriate actions. This article examines the communication barriers that emerge when transitioning from individual to team SA in emergency management scenarios. We observed two emergency exercises on “ongoing life-threatening violence” and dam failure causing hospital congestion. The study was complemented with interviews with participants of these exercises, aiming at identifying barriers called SA-demons in the team setting. We discovered barriers that hinder the establishment of team SA, including a vicious cycle of mistrust, a fragmented information trap, a false feeling of mastery trap, and a decaying memory trap. These barriers can stem from individual, organizational, or technological factors. To complement existing SA theories, we applied the Cynefin framework and found that standard operating procedures can be potential barriers when transitioning into chaotic or complex domains.
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Tasneem, F., Chakraborty, S., & Chy, A. N. (2023). An Early Synthesis of Deep Neural Networks to Identify Multimodal Informative Disaster Tweets. In Jaziar Radianti, Ioannis Dokas, Nicolas Lalone, & Deepak Khazanchi (Eds.), Proceedings of the 20th International ISCRAM Conference (pp. 428–438). Omaha, USA: University of Nebraska at Omaha.
Abstract: Twitter is always worthwhile in facilitating communication during disasters. It helps in raising situational awareness and undertaking disaster control actions as quickly as possible to alleviate the miseries. But the noisy essence of Twitter causes difficulty in distinguishing relevant information from the heterogeneous contents. Therefore, extracting informative tweets is a substantial task to help in crisis intervention. Analyzing only the text or image content of the tweet often misses necessary insights which might be helpful during disasters. In this paper, we propose a multimodal framework to address the challenges of identifying informative crisis-related tweets containing both texts and images. Our presented approach incorporates an early fusion strategy of BERT-LSTM and ResNet50 networks which effectively learns from the joint representation of texts and images. The experiments and evaluation on the benchmark CrisisMMD dataset show that our fusion method surpasses the baseline by 7% and substantiates its potency over the unimodal systems.
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Hannes Restel, Eridy Lukau, Sebastian Sterl, & Lars Gerhold. (2022). Detecting Covid-19 Relevant Situations using Privacy-by-Design based Mobile Experience Sampling. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 506–527). Tarbes, France.
Abstract: To observe psychosocial effects of the Covid-19 pandemic on the population, multiple retrospective studies have been performed in Germany. However, this approach may lead to response bias regarding affective and cognitive processes as it fails to capture situations as they occur (‘in situ’). Identifying those situations in daily life where individuals are emotionally and cognitively affected by Covid-19 can provide valuable insights for mobile experience sampling method studies (MESM) that evaluate participants’ affective and cognitive processes. This study presents an MESM solution (a self-developed smartphone app and server backend) to detect Covid-19 induced ‘in-situ frames’ which was successfully used in a long-term psychosocial study in Berlin (Germany) from November 2021 to January 2022. As highly sensitive personal data (e.g., emotional state, vaccination status and infection state, socio-demographics) have been collected, the solution places a strong emphasis on privacy, pseudo-anonymization, data-minimization, and security. To support long-time motivation for the participants, good usability and user experience containing gamification elements were also realized. The results indicate that Covid-19-related situations expressed by means of a high emotional risk perception could be identified even though participants located themselves in “rather Covid-19 free” private spaces.
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Eulalia Gomez Martin, Josune Hernantes, Leire Labaka, & Marcos Borges. (2022). Building upon the Existing Knowledge: Updating and Improving the Smart Mature Resilience Model. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 437–459). Tarbes, France.
Abstract: In recent years the concept of urban resilience has acquired great relevance within urban planning. The complexity of urban systems and the wide scope of the resilience concept require tools to facilitate the integration of the concept in urban development. Numerous studies, tools, and theoretical frameworks have been developed to support the resilient transformation of cities. However, these initiatives are usually not holistically integrated and limit incorporating the changes and advances in the resilience concept. This article highlights the importance of shifting from a continuously-building-new approach to building on an existing knowledge approach. This study has updated and improved the maturity model developed within the Horizon 2020 project Smart Mature Resilience. A bibliometric analysis was carried out to study the developments in resilience over the past four years and to integrate the relevant advances in the area into a new version of the Smart Mature Resilience Maturity Model (SMR MM).
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Alexander Gabriel, Babette Tecklenburg, & Frank Sill Torres. (2022). Threat and Risk Scenarios for Offshore Wind Farms and an Approach to their Assessment. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 162–173). Tarbes, France.
Abstract: Offshore wind farms in the German North and Baltic Seas have a key role to play in the context of the shift towards renewable energy and in securing electricity supplies in the future. At the same time, however, shipping routes in the North and Baltic Seas are among the busiest in the world, wind farms are increasingly being operated unmanned and conflicts increasingly involve a hybrid element. From these constellations and competing interests, various risk and threat scenarios emerge. By means of a survey among experts from offshore wind industry, this paper first captures the subjective assessment of the risk situation in order to subsequently develop an approach for their evaluation. The paper uses Bayesian networks in order to enable a risk assessment also under inclusion of uncertain parameters.
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