Integration of OPC UA Information Models into Enterprise Knowledge Graphs
More details
Hide details
Cyber-Physical Production Systems, Fraunhofer IWU, Germany
Arno Weiss   

Cyber-Physical Production Systems, Fraunhofer IWU, Reichenhainer Str. 88, 09126, Chemnitz, Germany
Submission date: 2022-01-31
Final revision date: 2022-04-14
Acceptance date: 2022-05-12
Online publication date: 2022-05-17
Publication date: 2022-06-28
Journal of Machine Engineering 2022;22(2):138–147
Building repositories of data relevant for enterprise operations requires harmonization of formats and semantics. OPC UA’s nodes-and-references data model shares basic elements with well-established semantic modeling technologies like RDF. This paper suggests the use of transformed OPC UA information models on the higher level of Enterprise Knowledge Graphs. It proposes good practice to integrate the separate domains by representing OPC UA servers as RDF-graphs and subsequently attaching them to Digital Twins embedded in Enterprise Knowledge Graph structures. The developed practice is implemented, applied to combine a server’s structure with an existing knowledge graph containing an Asset Administration Shell and released open source.
NILSSON J., SANDIN F., 2018, Semantic Interoperability in Industry 4.0: Survey of Recent Developments and Outlook, Proceedings IEEE 16th International Conference on Industrial Informatics (INDIN), Faculty of Engineering of the University of Porto, Portugal, 18–20 July 2018, IEEE, Piscataway, NJ, 127–132.
Industrial Internet Consortium, 2020, Digital Twins for Industrial Applications: Definition, Buisiness Values, Design Aspects, Standards and Use Cases. White Paper, Industrial_Apps_White_Paper_2020-02-18.pdf., Accessed 12 Aug 2021.
GALKIN M., AUER S., VIDAL M-E., et al., 2017, Enterprise Knowledge Graphs: A Semantic Approach for Knowledge Management in the Next Generation of Enterprise Information Systems, Hammoudi S, Smialek M, Camp O et al. (eds), Proceedings of the 19th International Conference on Enterprise Information Systems, 1, 26–29 April, Porto, Portugal, SCITEPRESS – Science and Technology Publications, SCITEPRESS, 88–98.
PAULHEIM H., 2016, Knowledge Graph Refinement: A Survey of Approaches and Evaluation Methods, SW 8, 489–508,
SCHIEKOFER R., GRIMM S., BRANDT M.M., et al., 2019, A Formal Mapping Between OPC UA and the Semantic Web, IEEE 17th International Conference on Industrial Informatics (INDIN), Aalto University, Helsinki-Espoo, Finland, 22–25 July, Proceedings, IEEE, Piscataway, NJ, 33–40.
SCHIEKOFER R., WEYRICH M., 2019, Querying OPC UA Information Models with SPARQL, 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), IEEE, 208–215.
PERZYLO A., PROFANTER S., RICKERT M., et al., 2019, OPC UA NodeSet Ontologies as a Pillar of Representing Semantic Digital Twins of Manufacturing Resources, 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), IEEE, 1085–1092.
STEINDL G., KASTNER W., 2021, Transforming OPC UA Information Models into Domain-Specific Ontologies, 4th IEEE International Conference on Industrial Cyber-Physical Systems (ICPS), Online, 10–13 May, IEEE, Piscataway, NJ, 191–196.
BAKKEN M., 2021, Quarry: An Open Source Tool for OPC UA SPARQL Queries Over Hybrid Architectures Using Query Rewriting, 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), IEEE, 1–7.
EHRLINGER L., WOLFRAM W., 2016, Towards a Definition of Knowledge Graphs, SEMANTiCS 2016, Posters and Demos Track, September 13-14, Leipzig, Germany.
BORGO S., LEITAO P., 2004, The Role of Foundational Ontologies in Manufacturing Domain Applications, Hutchison D., Kanade T., Kittler J., et al. (eds), On the Move to Meaningful Internet Systems 2004, CoopIS, DOA, and ODBASE, 3290, Springer Berlin Heidelberg, 670–688.
LEMAIGNAN S., SIADAT A., DANTAN J-Y., et al., 2006, MASON: A Proposal for an Ontology of Manufacturing Domain, Marik V. (ed), Proceedings DIS 2006, IEEE Workshop on Distributed Intelligent Systems, Collective Intelligence and its Applications, June 15–16, Prague, Czech Republic, IEEE, Piscataway, NJ, 195–200.
Verein Deutscher Ingenieure, 2011, Manufacturing Execution Systems (MES): Logic interfaces for machine and plant control, ICS 35.240.50 (VDI 5600, Sheet 3), Accessed 10 Oct 2021.
Plattform Industrie 4.0, 2020, Details of the Asset Administration Shell – Part 1: The Exchanges of Information between Partners in the Value Chain of Industrie 4.0, Downloads/Publikation/Details_of_the_Asset_Administration_Shell_Part1_V3.html, Accessed 04 Dec 2021.
BADER S.R., MALESHKOVA M., 2019, The Semantic Asset Administration Shell, Acosta Deibe M., Cudre-Mauroux P., Maleshkova M., et al. (eds), Semantic systems: The power of AI and knowledge graphs: 15th International Conference, SEMANTiCS 2019, Karlsruhe, Germany, September 9–12, Proceedings, 11702, Springer Open, Cham, Switzerland, 159–174.
JACOBY M., USLÄNDER T., 2020, Digital Twin and Internet of Things – Current Standards Landscape, Applied Sciences, 10, 6519,
Object Management Group, 2016, Meta Object Facility Specification: Version 2.5.1, MOF/, Accessed 06 Dec 2021.
OPC Foundation, 2021, OPC UA for Asset Administration Shell (AAS) OPC 30270, https://reference.opcfoundatio.... org/I4AAS/docs/. Accessed 06 Dec 2021.
BERNERS-LEE T., 2010, Linked Data – Design Issues,, Accessed 04 Dec 2021.
WILKINSON M., DUMONTIER M., AALBERSBERG I., et al., 2016, The FAIR Guiding Principles for Scientific Data Management and Stewardship, Sci Data 3, 160018,
Plattform Industrie 4.0, 2021, Details of the Asset Administration Shell - Part 2: Interoperability at Runtime – Exchanging Information via Application Programming Interfaces, Version 1.0RC02, Accessed 25 Nov 2021.