Ordnance Survey, the national mapping agency of Great Britain, is investigating how semantic web technologies assist its role as a geographical information provider. A major part of this work involves the development of prototype products and datasets in RDF. This article discusses the production of an example dataset for the administrative geography of Great Britain, demonstrating the advantages of explicitly encoding topological relations between geographic entities over traditional spatial queries. We also outline how these data can be linked to other datasets on the web of linked data and some of the challenges that this raises.is already evidence of how important GI is for the Web today, from the large investment of all three main search engine providers, Google, Microsoft and Yahoo!, in collecting GI to aid local search. A place name is one of the simplest forms of location information. Place names are often used in simple web searches such as: "Find me all pizza restaurants in Southampton", or "Find me holiday destinations in Cornwall". This suggests that gazetteers (indexes of place names) are a very useful addition to the semantic web. Geonames (http://sws.geonames.org/6269131/about.rdf), DBpedia (http://DBpedia.org/ page/England) and the CIA World Factbook (http://www4.wiwiss.fu-berlin.de/factbook/) are RDF datasets that include this type of information. However, none of these properly describes the official administrative geography of Great Britain as laid down by Parliamentary legislation though Statutory Instruments (House of Commons 2008), a resource that has already been requested by other RDF projects (Tennison and Sheridan 2008). With respect to geographical information, RDF does have a significant limitation in that it cannot support any form of spatial indexing. Thus the ability to spatially query GI in the traditional sense, or to perform many standard GIS operations such as buffering or containment within a user defined area, are either not possible, or would prove to be so computationally inefficient as to render them unusable. At this stage we see this as an important constraint on what is possible, but not as a reason to abandon RDF. Rather, we feel there are still significant advantages to using RDF for GI and, in time, we expect solutions to these limitations to emerge. Given our desire to investigate the representation of GI using RDF, the need for authoritative geographical names, and the limitations imposed by RDF in terms of spatial querying, we decided that a gazetteer representing the administrative areas of Britain would be the most appropriate form of geographical resource to investigate.The original description of the Semantic Web as outlined in Berners-Lee et al. (2001) was a vision of how software agents could understand the meaning of web content in order to find and process information across the web more accurately. The emergence of the Linked Open Data movement (Bizer et al. 2008b) or "web of data" from the original web of documents moves us further along the path towards ...

Abstract:The mathematical nature of description logics has meant that domain experts find them hard to understand. This forms a significant impediment to the creation and adoption of ontologies. This paper describes Rabbit, a Controlled Natural Language that can be translated into OWL with the aim of achieving both comprehension by domain experts and computational preciseness. We see Rabbit as complementary to OWL, extending its reach to those who need to author and understand domain ontologies but for whom descriptions logics are difficult to comprehend even when expressed in more user-friendly forms such as the Manchester Syntax.The paper outlines the main grammatical aspects of Rabbit, which can be broadly classified into declarations, concept descriptions and definitions, and elements to support interoperability between ontologies. The paper also describes the human subject testing that has been performed to date and indicates the changes currently being made to the language following this testing. Further modifications have been based on practical experience of the application of Rabbit for the development of operational ontologies in the domain of topography. Forest -and when I say thinking I mean thinking -you and I must do it." A. A. Milne

The process of authoring ontologies requires the active involvement of domain experts who should lead the process, as well as providing the relevant conceptual knowledge. However, most domain experts lack knowledge modelling skills and find it hard to follow logical notations in OWL. This paper presents ROO, a tool that facilitates domain experts' definition of ontologies in OWL by allowing them to author the ontology in a controlled natural language called Rabbit. ROO guides users through the ontology construction process by following a methodology geared towards domain experts' involvement in ontology authoring, and exploiting intelligent user interfaces techniques. An evaluation study has been conducted comparing ROO against another popular ontology authoring tool. Participants were asked to create ontologies based on hydrology and environment modelling scenarios related to real tasks at the mapping agency of Great Britain. The study is discussed, focusing on the usability and usefulness of the tool, and the quality of the resultant ontologies.

Abstract. This paper describes the development of a systematic method for creating domain ontologies. We have chosen to explicitly recognise the differing needs of the human domain expert and the machine in our representation of ontologies in two forms: a conceptual and a logical ontology. The conceptual ontology is intended for human understanding and the logical ontology, expressed in description logics, is derived from the conceptual ontology and intended for machine processing. The main contribution of our work is the division of these two stages of ontology development, with emphasis placed on domain experts themselves creating the conceptual ontology, rather than relying on a software engineer to elicit knowledge about the domain. In particular, this paper concentrates on the creation of conceptual ontologies and analyses the success of our methodology when tested by domain experts.

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