Maurizio Marchese, Lorenzino Vaccari, Pavel Shvaiko, & Juan Pane. (2008). An application of approximate ontology matching in eResponse. In B. V. de W. F. Fiedrich (Ed.), Proceedings of ISCRAM 2008 – 5th International Conference on Information Systems for Crisis Response and Management (pp. 294–304). Washington, DC: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Ontology matching is a key problem in many metadata intensive application domains, including emergency response, data integration, peer-to-peer information sharing, web service composition, and query answering on the web. In this paper we present an emergency response scenario based on the organizational model as used in Trentino region, Italy. We provide a formalization of this scenario with the help of lightweight coordination calculus. Then, we discuss an automatic approximate structure preserving matching algorithm which we applied within the emergency response scenario. The evaluation results, though preliminary, are encouraging.
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Nicholas Palmer, Roelof Kemp, Thilo Kielmann, & Henri Bal. (2012). RAVEN: Using smartphones for collaborative disaster data collection. 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: In this paper we describe our work in progress on RAVEN, a framework, which makes it possible to build applications for collaborative editing of structured data on Android. RAVEN offers developers compile time tools, which use only the schema to generate all database handling components, edit and list user interfaces, as well as those needed for data synchronization, significantly reducing development effort. In addition, RAVEN also offers the ability to do the same work, entirely at runtime, using only a smartphone. With RAVEN it is possible to construct data oriented applications on phone at any time, including during a disaster. Users can share their applications simply by sharing the database and corresponding schema. Thus, RAVEN enables completely decentralized application creation, sharing, and data distribution, avoiding issues of connectivity to centralized resources. In this paper we show that with RAVEN it is possible to construct a new application at runtime and compare the results with an equivalent custom-built application. © 2012 ISCRAM.
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