Integrating industrial middleware in Linked Data collaboration networks

Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/GutachtenBeitrag in KonferenzbandBeigetragenBegutachtung

Beitragende

Abstract

Within the Semantic Web field, Linked Data is an emerging technology offering advantages in terms of flexibility and openness also for industrial environments. It provides a powerful information model with simple extension mechanisms and a cross-domain character, which makes it possible to span flexible information spaces across enterprise boundaries. Thus, it is able to represent all facets of a digital plant, like devices and processes. Although developed with the focus on static data, it is also capable of handling dynamic data if the latter is adapted appropriately. This article describes these requirements and presents a concept for integrating process data into the Linked Data information space. A separation between a semantic description of the access to process data and the service providing exactly this information allows efficient and integration-ready access to data. The necessary vocabulary is described as well as the information model. A prototypical implementation of OPC UA integration into Linked Data is presented. The article further discusses the current status of the approach and provides future research challenges.

Details

OriginalspracheEnglisch
Titel2016 IEEE 21st International Conference on Emerging Technologies and Factory Automation, ETFA 2016
Herausgeber (Verlag)Institute of Electrical and Electronics Engineers (IEEE)
ISBN (elektronisch)9781509013142
PublikationsstatusVeröffentlicht - 3 Nov. 2016
Peer-Review-StatusJa

Publikationsreihe

ReiheInternational Conference on Emerging Technologies and Factory Automation (ETFA)
Band2016-November
ISSN1946-0740

Konferenz

Titel2016 21st IEEE International Conference on Emerging Technologies and Factory Automation
KurztitelETFA 2016
Veranstaltungsnummer21
Dauer6 - 9 September 2016
BekanntheitsgradInternationale Veranstaltung
StadtBerlin
LandDeutschland

Externe IDs

ORCID /0000-0001-5165-4459/work/172571750

Schlagworte

Forschungsprofillinien der TU Dresden

Fächergruppen, Lehr- und Forschungsbereiche, Fachgebiete nach Destatis

Ziele für nachhaltige Entwicklung

Schlagwörter

  • Linked Data, OPC UA, Process Data Integration, REST service, semantic middleware, Virtual Factory