Thomas Vögele

Ontologies for geographic information processing

The development of geographical information systems (GIS) and the interoperability between these systems demands new requirements for the description of the underlying data. The exchange of data between GIS systems is problematic and often fails due to confusion in the meaning of concepts. The term semantic translator, a translator between GIS systems and/or catalogue systems which gives the user the option to map data between the systems is a topic of current research. This paper provides an overview of formal ontologies and how they can be used for geographical information processing. A description of an intelligent broker architecture for semantic-based information retrieval is introduced, and shows how this approach can be used for general purposes. In conclusion we attempt to provide a roadmap for the use of ontologies for geographic information processing.

Qualitative Spatial Representation for Information Retrieval by Gazetteers

Intelligent and efficient information retrieval becomes increasingly important. Analogous to thesauri in the realm of spatial concepts, gazetteers offer a controlled vocabulary that can be used for spatial queries. Gazetteers use geographic footprints to link place names to geographic locations. Which geographic footprint representation is chosen has a strong impact on the quality of spatial queries. However, the footprint representations currently used in standard gazetteers such as points, lines, grid cell representations, and bounding boxes do not offer enough topological information to support refined spatial queries. We propose a new type of spatial footprint that can be described as a qualitative representation of the spatial decomposition of geographic entities. It holds enough topological and ordinal information enable refined spatial queries without being subject to the constraints of exact polygon representations. The proposed spatial representation was developed to be combined with terminological reasoning techniques used in systems for intelligent information integration.

Ontology-based search for interactive digital maps

Our main objective is to develop user-centric services to support better governance, democratic processes, and a sustainable and balanced development of rural and urban areas around the North Sea. A bike trip example offers a detailed look at the GeoShare Networks technologies, including ontologies for describing vocabularies and catalogs. We also discuss about the spatial data infrastructure consisting of a spatial reasoner, a Web catalog service, distributed Web map services, and a generic Web map client and about the ontology-based search for interactive digital maps.

Intelligent Brokering of Environmental Information with the BUSTER System

Many application areas of information systems share the need to store and process large amounts of diverse data, which is often geographically distributed. This implies that in order to make new data available to the system these data has to be transferred into the system’s specific data format. This is a very time consuming and tedious process. Data acquisition, automatically or semi-automatically, often requires large-scale investment in technical infrastructure and/or manpower. These obstacles are some of the reasons behind the concept of information sharing. Information sharing is attractive because in order to supplement an existing data basis remote information can be accessed by systems. The advantages of successful information sharing is thus obvious for many reasons: Quality improvement of data due to the availability of large and complete data. Quality improvement of data due to the availability of large and complete data. Avoidance of redundant data and conflicts that can arise from redundancy

Intuitive Modelling of Place Name Regions for Spatial Information Retrieval

Reasoning about spatial relevance is important for intelligent spatial information retrieval. In heterogeneous and distributed systems like the Semantic Web, spatial reasoning has to be based on light-weight, interoperable and easy-to-use spatial metadata.

Indexing and Browsing Digital Maps with Intelligent Thumbnails

With the increasing number of digital maps and other geo-referenced data that are available over the Internet, there is a growing need for access to techniques that allow us to preview the content and to evaluate it relative to the requirements for complex spatial and thematic queries. Analogous to the digital indices for fulltext searches on text documents we introduce highly condensed, machinereadable indices of digital maps. The purpose of these “intelligent thumbnails“ is to support sophisticated queries of the type concept@location. An intelligent thumbnail is based on a projection of the thematic content of a digital map onto a standard reference tessellation. To make the thumbnail exchangeable in a distributed and heterogeneous environment, the underlying Standard Reference Tessellation (SRT) is qualitatively abstracted from a polygonal representation to a connection graph. In combination with a hierarchical place name structure and concept ontology, it is used to evaluate the spatial and thematic relevance of the indexed data sources with respect to spatio-thematic queries.