ISCRAM Digital Library -- Query Results

Joeri van Laere, & Kristens Gudfinnsson. (2022). Continuous Systematic Situation Monitoring: Pitfalls and Possibilities. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 460–468). Tarbes, France. Abstract: Situation pictures are helpful to make sense of what is happening and to prevent further escalation. These situation pictures are typically text- or map-based and focus on the current effects of the crisis. For long-lasting transboundary crises that impact many critical infrastructures and different parts of society directly and indirectly, such situation pictures have limitations. Crisis management teams might benefit from continuous monitoring of societal performance indicators, so the current situation can easily be compared with historical and future data to reveal trends and escalations. This research project explored how a successful approach for systematic monitoring of indicators in crime prevention could be transferred to crisis management. Several pilot studies revealed nine challenging pitfalls and six promising possibilities. The findings of this study can inform future research on how continuous systematic situation monitoring can strengthen societal resilience. Keywords: Situation awareness; indicators; monitoring; Business Intelligence; Business Continuity Management Track: Data and Resilience: Opportunities and Challenges http://idl.iscram.org/show.php?record=2432
Tanaporn Panrungsri, & Esther Sangiamkul. (2017). Business Intelligence Model for Disaster Management: A Case Study in Phuket, Thailand. 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 (pp. 727–738). Albi, France: Iscram. Abstract: This research presents the conceptual Business Intelligence (BI) model for disaster management. BI can provide agility capacity for decision making in dynamic environment among different agencies. This project designs and develop a data warehouse using multi-dimensional model for severity analysis of flood and landslide in risk area using case study from Department of disaster prevention and mitigation (DDMP), Phuket, Thailand. The concept of BI can be applied for extremely heterogeneous data structures and data platform environment to improve data quality and expose to better decision-making for disaster management. In the next stage of this project, we will integrate more data sources from other agencies for example GIS data from Phuket land-use planning and flooding prediction model database. The result of this study will help organization deploy BI more effectively. Keywords: Business Intelligence; data warehousing; decision support system; conceptual model; disaster management Track: Operational applications and perspectives http://idl.iscram.org/show.php?record=2060
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. Keywords: Emergency Management, Natural Disasters, Dashboards, Business Intelligence, Decision Support Systems. Track: 1st International Workshop on Intelligent Crisis Management Technologies for Climate Events (ICMT) http://idl.iscram.org/show.php?record=2183

Joeri van Laere, & Kristens Gudfinnsson. (2022). Continuous Systematic Situation Monitoring: Pitfalls and Possibilities. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 460–468). Tarbes, France.

Tanaporn Panrungsri, & Esther Sangiamkul. (2017). Business Intelligence Model for Disaster Management: A Case Study in Phuket, Thailand. 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 (pp. 727–738). Albi, France: Iscram.

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.