Title: The Semantic Asset Administration Shell
Authors: Bader, Sebastian R.
Maleshkova, Maria 
Language: eng
Keywords: Asset Administration Shell;Data lifting;Industrie 4.0
Issue Date: Nov-2019
Publisher: Springer
Document Type: Book Part
Journal / Series / Working Paper (HSU): Lecture Notes in Computer Science
Volume: 11702
Page Start: 159
Page End: 174
Publisher Place: Cham
Conference: 15th International Conference, SEMANTiCS 2019, Karlsruhe, Germany, September 9–12, 2019
Abstract: 
The disruptive potential of the upcoming digital transformations for the industrial manufacturing domain have led to several reference frameworks and numerous standardization approaches. On the other hand, the Semantic Web community has made significant contributions in the field, for instance on data and service description, integration of heterogeneous sources and devices, and AI techniques in distributed systems. These two streams of work are, however, mostly unrelated and only briefly regard the each others requirements, practices and terminology. We contribute to this gap by providing the Semantic Asset Administration Shell, an RDF-based representation of the Industrie 4.0 Component. We provide an ontology for the latest data model specification, created a RML mapping, supply resources to validate the RDF entities and introduce basic reasoning on the Asset Administration Shell data model. Furthermore, we discuss the different assumptions and presentation patterns, and analyze the implications of a semantic representation on the original data. We evaluate the thereby created overheads, and conclude that the semantic lifting is manageable, also for restricted or embedded devices, and therefore meets the conditions of Industrie 4.0 scenarios.
Organization Units (connected with the publication): Universität Bonn
ISBN: 9783030332198
ISSN: 03029743
Publisher DOI: 10.1007/978-3-030-33220-4_12
Appears in Collections:6 - Publication references (only metadata) of your publications before HSU

Show full item record

CORE Recommender

SCOPUSTM   
Citations

32
checked on Feb 21, 2024

Google ScholarTM

Check

Altmetric

Altmetric


Items in openHSU are protected by copyright, with all rights reserved, unless otherwise indicated.