Steindl, Gernot

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Ontology-Based Model Identification of Industrial Energy Systems
(2020)
Scopus© Citations 4 12
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Generic Digital Twin Architecture for Industrial Energy Systems
(2020-12-13)
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Stagl, Martin
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Kasper, Lukas
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Kastner, Wolfgang
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Hofmann, Rene
Scopus© Citations 147 1
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Semantic Microservice Framework for Digital Twins
(2021-06-18)
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Kastner, Wolfgang
Scopus© Citations 37 9
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Deriving semantic validation rules from industrial standards: An OPC UA study
(2023-06-19)
Bareedu, Yashoda Saisree
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Frühwirth, Thomas
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Niedermeier, Christoph
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Sabou, Marta
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Industrial standards provide guidelines for data modeling to ensure interoperability between stakeholders of an industry branch (e.g., robotics). Most frequently, such guidelines are provided in an unstructured format (e.g., pdf documents) which hampers the automated validations of information objects (e.g., data models) that rely on such standards in terms of their compliance with the modeling constraints prescribed by the guidelines. This raises the risk of costly interoperability errors induced by the incorrect use of the standards. There is, therefore, an increased interest in automatic semantic validation of information objects based on industrial standards. In this paper we focus on an approach to semantic validation by formally representing the modeling constraints from unstructured documents as explicit, machine-actionable rules (to be then used for semantic validation) and (semi-)automatically extracting such rules from pdf documents. While our approach aims to be generically applicable, we exemplify an adaptation of the approach in the concrete context of the OPC UA industrial standard, given its large-scale adoption among important industrial stakeholders and the OPC UA internal efforts towards semantic validation. We conclude that (i) it is feasible to represent modeling constraints from the standard specifications as rules, which can be organized in a taxonomy and represented using Semantic Web technologies such as OWL and SPARQL; (ii) we could automatically identify modeling constraints in the specification documents by inspecting the tables ( P = 87 %) and text of these documents (F1 up to 94%); (iii) the translation of the modeling constraints into formal rules could be fully automated when constraints were extracted from tables and required a Human-in-the-loop approach for constraints extracted from text.
12
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SigSPARQL: Signals as a First-Class Citizen when Querying Knowledge Graphs1
(2025-08-26)
Schwarzinger, Tobias
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Frühwirth, Thomas
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Preindl, Thomas
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14
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Ten questions concerning building information modeling (BIM): Energy-efficiency in design, construction, and operation
(2026-05)
Hammes, Sascha
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Zech, Philipp
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Geisler-Moroder, David
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Weninger, Johannes
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Scopus© Citations 3 7
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An Iterative Lifecycle Model for Engineering and Operating Digital Twins
(2026)
Klaassen, Christoph
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Hofmann, René
1
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Utilizing Large Language Models for Automated Log-Based Thing Description Generation1
(2025-08-26)
Thoma, Max
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Esterbauer, Leonhard
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Preindl, Thomas
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7
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Digital Twinning for Industrial Energy Systems Utilizing Semantic Web Technologies
(2022)
Future industrial energy systems have to adapt to new requirements, caused by a flexible production environment, the usage of volatile renewable energy sources, and the integration into energy markets. Consider these energy systems as Industrial Cyber-Physical Systems (ICPSs), Digital Twins (DTs) are the key enabling technology for optimizing the operation by providing services for advanced monitoring, diagnosis, prediction, and control. Although the concept of DTs is not new, there are still missing architectural patterns and methods for creating them and their services in the domain of industrial energy systems efficiently. As an outcome, the thesis provides architectural guidelines for creating DTs and their services in the domain of industrial energy systems, considering RAMI 4.0 and utilizing existing OPC UA infrastructures to provide context information and run-time data stored in a federated knowledge graph. Therefore, a generic DT architecture is presented and a method is shown, how existing OPC UA information models can be used to instantiate domain-specific ontologies to provide context information for a DT. Also, an ontology- based data access method for OPC UA run-time data is developed to integrate time series data into a knowledge graph. The query performance of the developed approach is evaluated in comparison with other semantic sensor data integration methods. To showcase the applicability of the stored context information, the information is used to identify a data-driven simulation model automatically. In the end, functional and non- functional requirements and a service framework architecture for DTs are presented. The results of the thesis show the benefits of combining OPC UA and Semantic Web technology in the context of an architectural DT framework by making the DT adaptable to its environment and providing semantic interoperability between the DT’s services.
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A Methodology to Convert Tacit Knowledge into Explicit Knowledge - Smart Building Use Case
(2024-12-17)
Bilal, Mohammad
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Thoma, Max
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Kastner, Wolfgang
Scopus© Citations 1 12

Steindl, Gernot

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