Semantic technologies for describing measurement data in databases

Abstract

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.

Original document

The different versions of the original document can be found in:

• https://link.springer.com/content/pdf/10.1007%2F978-3-642-21064-8_14.pdf

• http://link.springer.com/content/pdf/10.1007/978-3-642-21064-8_14,

http://dx.doi.org/10.1007/978-3-642-21064-8_14 under the license http://www.springer.com/tdm

• https://link.springer.com/content/pdf/10.1007%2F978-3-642-21064-8_14.pdf,

https://elib.dlr.de/79606,

https://link.springer.com/chapter/10.1007%2F978-3-642-21064-8_14,

https://core.ac.uk/display/31003421,

https://www.scipedia.com/public/Noyer_et_al_2011a,

https://dblp.uni-trier.de/db/conf/esws/eswc2011-2.html#NoyerBK11,

https://academic.microsoft.com/#/detail/88229429