Data Integration in the Geospatial Semantic Web

Data Integration in the Geospatial Semantic Web

Patrick Maué (Westfälische Wilhelms-Universität Münster, Germany) and Sven Schade (Westfälische Wilhelms-Universität Münster, Germany)
Copyright: © 2009 |Pages: 23
DOI: 10.4018/jcit.2009072105
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Geospatial decision makers have to be aware of the varying interests of all stakeholders. One crucial task in the process is to identify relevant information available from the Web. In this chapter the authors introduce an application in the quarrying domain which integrates Semantic Web technologies to provide new ways to discover and reason about relevant information. The authors discuss the daily struggle of the domain experts to create decision-support maps helping to find suitable locations for opening up new quarries. After explaining how semantics can help these experts, they introduce the various components and the architecture of the software which has been developed in the European funded SWING project. In the last section, the different use cases illustrate how the implemented tools have been applied to real world scenarios.
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A careful assessment and selection of relevant information retrieved from the World Wide Web (WWW) is crucial for potentially precarious decision making tasks. Geographical (or geospatial) data created by national mapping agencies or globally acting companies is the relevant information in the case of geospatial decision making. Such information is most often served as compiled and sometimes interactive maps. Processing such data, for example to run a geospatial analysis, requires raw data. Using a case example from the mining industry, we are going to explain in this chapter how Semantic Web technologies facilitate the task of finding such geospatial data sets and assessing their usefulness for the intended application. We also show how semantics simplify loading and visualizing of this data using generic desktop clients.

Geospatial decision making requires the acquisition of relevant data sets beforehand (Longley et al., 2005). The notion of Geographic Information Retrieval (GIR) (Larson, 1996) is commonly used to summarize all the tasks needed to acquire geospatial data from the WWW by using search engines or catalogs implemented especially for managing such data. Most information is captured in form of text-based documents, which makes searching using keywords and text-indexing search engines very efficient. Geospatial data comes with additional dimensions: Space, i.e. the geographical extent of the represented entities, is one apparent characteristic. Special catalogs have been implemented to deal with the spatial component of such data by adding interactive maps to search dialogs. Time is another important aspect (Longley et al., 2005). The data yields information about entities or phenomena in the real world which is continuously moving on in time and changing its state. Hence, making geospatial data available in the Web poses various challenges to the data provider. The major standardization organization in the domain of geospatial applications, the Open Geospatial Consortium (OGC), introduced standardized catalog interfaces which support basic GIR functionalities. Instances of these catalogs are, together with other OGC-conformal Web Services serving or processing geospatial data, embedded in Spatial Data Infrastructures (SDI). In (Nebert, 2004) the basic principles of SDIs are introduced; various components of SDI and the potential benefits of Semantic Web technologies are further discussed later in this chapter.

Standards specifying how to access and use GIR systems are limited to the technical level. They define how to encode the queries, what parameters are allowed, and which operations the catalog should implement. They do not, however, suggest how a user formulates the query. The properties of geospatial data (space, time, and theme) can all be individually queried. But the task of asking the right question to retrieve this information is still a challenging one. It seems to be so simple, though. A user defines a region by drawing a box on a map, selects a point in time using a calendar, and specifies a theme by choosing a category or typing in some search terms. But especially keywords and categories suffers from the information asymmetry (Akerlof, 1970) between the searching user and the data provider. Language is, by nature, ambiguous and imprecise. Semantic conflicts (i.e. heterogeneities) and varying background knowledge impair every discovery task and can decrease the usefulness of the GIR system tremendously. And the success of systems depending on user interaction is measured by its usefulness.

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