Building a Knowledge Graph with Inference for a Production Machine Using the Web of Things Standard
Meckler S, Steinmüller H, Harth A (2021)
Publication Type: Conference contribution
Publication year: 2021
Journal
Publisher: Springer Science and Business Media Deutschland GmbH
Book Volume: 12799 LNAI
Pages Range: 240-251
Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISBN: 9783030794620
DOI: 10.1007/978-3-030-79463-7_20
Abstract
This paper presents an architecture for a knowledge-based system (KBS) that consists of a Knowledge Graph, an inference engine and services. The Web of Things standard is used to translate sensor data from a production machine into an RDF graph. The KBS architecture is implemented for a physical twin of a real machine using open-source Semantic Web technologies. The performance evaluation of the system reveals limitations for the application in production.
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Germany (DE)How to cite
APA:
Meckler, S., Steinmüller, H., & Harth, A. (2021). Building a Knowledge Graph with Inference for a Production Machine Using the Web of Things Standard. In Hamido Fujita, Ali Selamat, Jerry Chun-Wei Lin, Moonis Ali (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 240-251). Springer Science and Business Media Deutschland GmbH.
MLA:
Meckler, Sascha, Harald Steinmüller, and Andreas Harth. "Building a Knowledge Graph with Inference for a Production Machine Using the Web of Things Standard." Proceedings of the 34th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2021 Ed. Hamido Fujita, Ali Selamat, Jerry Chun-Wei Lin, Moonis Ali, Springer Science and Business Media Deutschland GmbH, 2021. 240-251.
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