Efstratios Kontopoulos, Panagiotis Mitzias, Jürgen Moßgraber, Philipp Hertweck, Hylke van der Schaaf, Désirée Hilbring, et al. (2018). Ontology-based Representation of Crisis Management Procedures for Climate Events. In Kees Boersma, & Brian Tomaszeski (Eds.), ISCRAM 2018 Conference Proceedings – 15th International Conference on Information Systems for Crisis Response and Management (pp. 1064–1073). Rochester, NY (USA): Rochester Institute of Technology.
Abstract: One of the most critical challenges faced by authorities during the management of a climate-related crisis is the overwhelming flow of heterogeneous information coming from humans and deployed sensors (e.g. cameras, temperature measurements, etc.), which has to be processed in order to filter meaningful items and provide crisis decision support. Towards addressing this challenge, ontologies can provide a semantically unified representation of the domain, along with superior capabilities in querying and information retrieval. Nevertheless, the recently proposed ontologies only cover subsets of the relevant concepts. This paper proposes a more “all-around” lightweight ontology for climate crisis management, which greatly facilitates decision support and merges several pertinent aspects: representation of a crisis, climate parameters that may cause climate crises, sensor analysis, crisis incidents and related impacts, first responder unit allocations. The ontology could constitute the backbone of the decision support systems for crisis management.
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Dirk Fahland, Timo Mika Gläßer, Bastian Quilitz, Stephan Weißleder, & Ulf Leser. (2007). HUODINI-flexible information integration for disaster 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. 255–262). Delft: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Fast and effective disaster management requires access to a multitude of heterogeneous, distributed, and quickly changing data sets, such as maps, satellite images, or governmental databases. In the last years, also the information created by affected persons on web sites such as flickr.com or blogger.com became an important and very quickly adapting source of information. We developed HUODINI, a prototype system for the flexible integration and visu-alization of heterogeneous data sources for disaster management. HUODINI is based on Semantic Web technologies, and in particular RDF, to offer maximal flexibility in the types of data sources it can integrate. It supports a hybrid push/pull approach to cater for the requirements of fast-changing sources, such as news feeds, and maximum performance for querying the integrated data set. In this paper, we describe the design goals underlying our approach, its architecture, and report on first experiences with the system.
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