Print Email Facebook Twitter Semantic annotation of existing geo-datasets: A case study of disaster response in Netherlands Title Semantic annotation of existing geo-datasets: A case study of disaster response in Netherlands Author Mobasheri, A. Van Oosterom, P.J.M. Zlatanova, S. Bakillah, M. Faculty Applied Sciences Department OTB Research Date 2013-05-29 Abstract Use of relevant geo-information is one of the important issues for performing different tasks and processes in disaster response phase. In order to save time and cost, services could be employed for integrating and extracting relevant up-to-date geo-information. For this purpose, semantics of geo-information should be explicitly defined. This paper presents our initial results in applying an approach for semantic annotation of existing geo-datasets. In this research the process of injecting semantic descriptions into geodatasets (information integration) is called semantic annotation. A web system architecture is presented and the process of semantic annotation is presented by using the Meta Annotation approach. The approach is elaborated by providing an example in disaster response which utilizes geo-datasets in CityGML format and further two languages of semantic web technology: RDF and Notation3. Subject geo-informationsemantic webontologydisaster responseCityGML To reference this document use: http://resolver.tudelft.nl/uuid:1c30595e-220c-4bee-bcb4-67a729d197ba DOI https://doi.org/10.5194/isprsarchives-XL-4-W1-119-2013 Publisher International Society of Photogrammetry and Remote Sensing (ISPRS) ISSN 1682-1777 Source UDMS 2013: 29th Urban Data Management Symposium, London, UK, 29-31 May 2013; International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-4/W1, 2013 Part of collection Institutional Repository Document type conference paper Rights (c) 2013 The Author(s)This work is distributed under the Creative Commons Attribution 3.0 License. Files PDF Mobasheri_2013.pdf 335.76 KB Close viewer /islandora/object/uuid:1c30595e-220c-4bee-bcb4-67a729d197ba/datastream/OBJ/view