Disaster planning using automated composition of semantic OGC web services: A case study in sheltering

Spatial data are crucial in disaster planning. However, because of the dynamic, urgent and uncertain nature of disasters, certain data and functionalities may be inaccessible to decision makers when they are required. Web service composition offers a possible solution whereby disaster planners can integrate spatial web services to generate new spatial data and functionalities, quickly, from existing ones. This paper proposes an automatic solution for composing OWSs (Open Geospatial Consortium Web Services) for disaster planning. A semantic annotation approach based on the Resource Description Framework (RDF) and SPARQL languages is used to describe OWSs semantically. A conceptual model for AI (Artificial Intelligence) planning is also proposed that works based on RDF and SPARQL. An AI planning algorithm was implemented based on the proposed conceptual model to compose semantic OWSs. The applicability of the proposed solution is investigated through a case study in evacuation sheltering. The case study demonstrates that the proposed automatic composition approach can enhance the efficiency of OWS integration and thereby improve the disaster management process.