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Ontology-based information modelling in the industrial data space

 
: Pullmann, Jaroslav; Petersen, Niklas; Mader, Christian; Lohmann, Steffen; Kemény, Zsolt

:
Preprint urn:nbn:de:0011-n-4814132 (732 KByte PDF)
MD5 Fingerprint: fca244f75d5bcc3cc3b92b76c423e9d4
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Erstellt am: 9.3.2019


Institute of Electrical and Electronics Engineers -IEEE-:
ETFA 2017, 22nd IEEE International Conference on Emerging Technologies and Factory Automation : 12-15 September 2017, Limassol, Cyprus
Piscataway, NJ: IEEE, 2017
ISBN: 978-1-5090-6505-9
ISBN: 978-1-5090-6504-2
ISBN: 978-1-5090-6506-6
8 S.
International Conference on Emerging Technologies and Factory Automation (ETFA) <22, 2017, Limassol/Cyprus>
Englisch
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IAIS ()
Fraunhofer FIT ()

Abstract
The role and economic value of data has constantly evolved since the early information system ages. Likewise, the capabilities of data storage, processing and analysis have increased. In order to unlock the potential for inception of smart, data-driven services and novel value creation chains, a means for trustful data exchange that ensures traceability as well as the data owner's privacy and sovereignty is particularly important in the industrial domain. However, widely accepted standardized solutions that fulfill these requirements are still missing. The Industrial Data Space initiative addresses this deficiency by the specification and implementation of a reference architecture model that supports reliable data exchange within a virtual data space. In this paper, we present an ontology-based information model that declaratively describes the static and dynamic properties of entities involved in interactions within the Industrial Data Space. We contribute a conceptual model that serves as a central, unifying contract for data exchange, and show how it can be applied in the context of an industrial scenario.

: http://publica.fraunhofer.de/dokumente/N-481413.html