Noyer et al 2011a - Revision history

Scipediacontent at 12:44, 21 January 2021

2021-01-21T12:44:40Z

Scipediacontent: Scipediacontent moved page Draft Content 666813399 to Noyer et al 2011a

2020-10-14T12:59:31Z

Scipediacontent moved page Draft Content 666813399 to Noyer et al 2011a

Scipediacontent: Created page with " == 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 appl..."

2020-10-14T12:59:28Z

Created page with " == 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 appl..."

New page

== 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.\r \r 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.

Document type: Part of book or chapter of book

== Full document ==
<pdf>Media:Draft_Content_666813399-beopen683-4359-document.pdf</pdf>

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

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 == 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.\r \r 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.
+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.
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-Document type: Part of book or chapter of book
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-== Full document ==
-<pdf>Media:Draft_Content_666813399-beopen683-4359-document.pdf</pdf>
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 * [https://link.springer.com/content/pdf/10.1007%2F978-3-642-21064-8_14.pdf https://link.springer.com/content/pdf/10.1007%2F978-3-642-21064-8_14.pdf]

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