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Development of context-aware applications is inherently complex. These applications adapt to changing context information: physical context, computational context , and user context/tasks. Context information is gathered from a variety of sources that differ in the quality of information they produce and that are often failure prone. The pervasive computing(More)
Semantic Web technologies, most notably RDF, are well-suited to cope with typical challenges in spatial data management including analyzing complex relations between entities, integrating heterogeneous data sources and exploiting poorly structured data, e.g., from web communities. Also, RDF can easily represent spatial relationships, as long as the location(More)
Many pervasive computing applications need sensor data streams, which can vary significantly in accuracy. Depending on the application, deriving information (e.g., higher-level context) from low-quality sensor data might lead to wrong decisions or even critical situations. Thus, it is important to control the quality throughout the whole data stream(More)