Integrating Scientific Data through External, Concept-Based Annotations
Proceedings of the VLDB 2002 Workshop EEXTT and CAiSE 2002 Workshop DTWeb on Efficiency and Effectiveness of XML Tools and Techniques and Data Integration over the Web-Revised Papers
Kepler: An Extensible System for Design and Execution of Scientific Workflows
SSDBM '04 Proceedings of the 16th International Conference on Scientific and Statistical Database Management
Semantic Web Information Management: A Model-Based Perspective
Semantic Web Information Management: A Model-Based Perspective
Query Answering for OWL-DL with rules
Web Semantics: Science, Services and Agents on the World Wide Web
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Exploration and analysis of vast empirical data is a cornerstone of the development and assessment of driver assistance systems. A common challenge is to apply the domain specific knowledge to the (mechanised) data handling, pre-processing and analysis process. Ontologies can describe domain specific knowledge in a structured way that is manageable for both humans and algorithms. This paper outlines an architecture to support an ontology based analysis process for data stored in databases. Build on these concepts and architecture, a prototype that handles semantic data annotations is presented. Finally, the concept is demonstrated in a realistic example. The usage of exchangeable ontologies generally allows the adaption of presented methods for different domains.