Integrating industrial middleware in Linked Data collaboration networks

Research output: Contribution to book/Conference proceedings/Anthology/ReportConference contributionContributedpeer-review

Contributors

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

Original languageEnglish
Title of host publication2016 IEEE 21st International Conference on Emerging Technologies and Factory Automation, ETFA 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (electronic)9781509013142
Publication statusPublished - 3 Nov 2016
Peer-reviewedYes

Publication series

SeriesInternational Conference on Emerging Technologies and Factory Automation (ETFA)
Volume2016-November
ISSN1946-0740

Conference

Title21st IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2016
Duration6 - 9 September 2016
CityBerlin
CountryGermany

External IDs

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

Keywords

Research priority areas of TU Dresden

DFG Classification of Subject Areas according to Review Boards

Subject groups, research areas, subject areas according to Destatis

Keywords

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