Schema Visualisation using a Metadata Approach for GIS Extended Abstract

A major requirement for using a GIS effectively is the ability to visualise the geographic datasets that are available for manipulation and analysis. Such geographic datasets may have been obtained from various sources and provided in the form of map data files in vector or raster formats. In general, a map file would represent a specific area in space and in the case of digitised vector data will contain information on a particular class of features in space, e.g. roads, rivers, land-use, etc. To be able to use the map files effectively, the user will need some means of identifying their contents. In particular the type of data, the spatial extent or location of the data in space, as well as other meta-data such as, the scale of the map and date the data has been acquired. In addition, to be able to manipulate the information contained in more than one map, it is important to view how the maps are related in space, e.g. whether they are overlapping partially or wholly. In traditional databases, a schema or a data model is the means of representing the objects, their properties and their relationships in the database. GIS are often characterised as being data rich but schema poor. In particular, it is often no

An Evaluation of Geo-Ontology Representation Languages for Supporting Web Retrieval of Geographical Information

The internet is the single largest information resource in the world. It is, however, not being used to is full potential. Currently most the information is written using syntactical machine readable languages such as HTML. These languages are limited in that they are only intended for human consumption. To fully unlock the potential of such a vast resource of information, we need to make the information not only machine readable but machine-understandable. In order to gain machine understanding we need semantic languages which are able to define meaning to the information being stored. Agents (human or machine) could then use this information in variety of different ways. A large amount of geographical information is currently being stored and delivered over the internet. Internet providers such as the Ordnance Survey are realizing the potential and are currently offering their data in GML format. Geographic digital libraries, such as the ADL, are being established. There is, however, the need to realize the potential of semantically enriching the geographic information to provide more automated and intelligent ways of managing and retrieving the data over the web. In February 2001 the semantic web initiative was launched by W3C (W3C, 2001) for the semantic representation of data on the Web. Tim Berners Lee, the creator of the World Wide Web, is quoted as saying `The Semantic Web is an extension of the current web in which information is given well-defined meaning, better enabling computers and people to work in cooperation'. In order for the semantic web to function, computers need access to structured information and inference rules. Key to this is the use of ontologies. An ontology is a specification of a conceptualization, which provides the structured vocabulary a..

A General Method for Spatial Reasoning in Spatial Databases

Qualitative spatial reasoning is important in large spatial databases. It is based on the manipulation of qualitative spatial relationships and used to derive new spatial knowledge. Spatial reasoning has so far been studied only for simple areal objects. Spatial databases usually consists of objects of different types and complexity. In this paper, a general reasoning approach is proposed for deriving the composition of topological relationships between spatial objects of arbitrary complexity in any space dimension. The reasoning rules proposed are used to derive a new composition table between different types of spatial objects. The approach is a step towards the development of general spatial reasoning engine for handling different types of spatial relations in spatial databases. 1 Introduction 1 Spatial databases such as geographic databases in Geographic Information Systems (GIS), geometric databases in CAD, or image databases in Multimedia Information Systems and Medical Inform..