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Syed Imran, Franclin Foping, Ioannis M. Dokas, & John Feehan. (2010). Towards domain specific modeling approach in early warning system. In C. Zobel B. T. S. French (Ed.), ISCRAM 2010 – 7th International Conference on Information Systems for Crisis Response and Management: Defining Crisis Management 3.0, Proceedings. Seattle, WA: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: It is of practical significance and great value to design and develop a novel Early Warning System (EWS), which will be used by the personnel of institutions involved in the drinking water delivery governance model of Ireland. In order to help the users of our EWS in representing and codifying their knowledge on the complex coincidences that may drive Water Treatment Plants (WTP) to failures or to hazardous states we propose in this paper a novel approach of using Domain Specific Modeling (DSM) in the domain of EWS for Water Treatment Plants. The novelty of our DSM approach also lies in providing a standalone open source software application rendering profiling of the water utilities, early warning signals, monitoring mechanisms of signals along with capability of assessing the “tendency” of a WTP towards failure, given a set of observed early warning signals.
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Kenny Meesters, & Thijs van Beek. (2021). Towards a tailor-made modelling language for information flow setups in humanitarian crisis management. 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. 448–458). Blacksburg, VA (USA): Virginia Tech.
Abstract: Over the years many different strategies, approaches and tools have been used in emergency response to connect information flows. In large-scale emergencies different tools, processes and structures are used to coordinate information. This is in part due to the differences in countries, emergencies, and local context, but also personal preferences, capabilities and resources play a role. Despite these differences, being able to compare and contrast various information structures, processes and systems would be beneficial to identify recurring structures and their performance. Modelling languages have been used in many other contexts to support these practices of describing, analyzing and comparing processes. This research examines the need and potential of a tailored modelling language to visualize information flow setups. In this study an initial set of requirements is developed from a literature study and further validated with expert in-depth interview. These requirements are compared with existing modelling languages to identify key building blocks of the language. The results provide key considerations for the development of a new modelling language to describe information flows in a consistent and structured manner.
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Don J.M. Willems, & Louis Vuurpijl. (2007). Designing interactive maps for crisis management. In K. Nieuwenhuis P. B. B. Van de Walle (Ed.), Intelligent Human Computer Systems for Crisis Response and Management, ISCRAM 2007 Academic Proceedings Papers (pp. 159–166). Delft: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: This paper describes the design, implementation, and evaluation of pen input recognition systems that are suited for so-called interactive maps. Such systems provide the possibility to enter handwriting, drawings, sketches and other modes of pen input. Typically, interactive maps are used to annotate objects or mark situations that are depicted on the display of video walls, handhelds, PDAs, or tablet PCs. Our research explores the possibility of employing interactive maps for crisis management systems, which require robust and effective communication of, e.g., the location of objects, the kind of incidents, or the indication of route alternatives. The design process described here is a mix of “best practices” for building perceptive systems, combining research in pattern recognition, human factors, and human-computer interaction. Using this approach, comprising data collection and annotation, feature extraction, and the design of domain-specific recognition technology, a decrease in error rates is achieved from 9.3% to 4.0%.
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Dimitris Zisiadis, Spyros Kopsidas, Vassilis Grizis, George Thanos, George Leventakis, & Leandros Tassiulas. (2012). STAR-TRANS Modeling Language (STML) modeling risk in the STAR-TRANS risk assessment framework for interconnected transportation systems. In Z.Franco J. R. L. Rothkrantz (Ed.), ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management. Vancouver, BC: Simon Fraser University.
Abstract: The present paper introduces a high level modeling language, capable of expressing the concepts and processes of the Strategic Risk Assessment and Contingency Planning in Interconnected Transportation Networks (STAR-TRANS) framework. STAR-TRANS is a comprehensive transportation security risk assessment framework for assessing related risks that provides cohered contingency management procedures for interconnected, interdependent and heterogeneous transport networks. STAR-TRANS modeling Language (STML) is a domain specific language combining language simplicity with a very clear syntax, providing all the necessary elements (assets, threats, incidents, consequences etc.) to model the STAR-TRANS risk assessment framework. © 2012 ISCRAM.
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