An agent composition framework for the J-Park simulator - a knowledge graph for the process industry
Digital twins, Industry 4.0 and Industrial Internet of Things are becoming ever more important in the process industry. The Semantic Web, linked data, knowledge graphs and web services/agents are key technologies for implementing the above concepts. In this paper, we present a comprehensive semantic...
| Main Authors: | , , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2021
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| Online Access: | https://hdl.handle.net/10356/152235 |
| _version_ | 1824456203934105600 |
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| author | Zhou, Xiaochi Eibeck, Andreas Lim, Mei Qi Krdzavac, Nenad B. Kraft, Markus |
| author2 | School of Chemical and Biomedical Engineering |
| author_facet | School of Chemical and Biomedical Engineering Zhou, Xiaochi Eibeck, Andreas Lim, Mei Qi Krdzavac, Nenad B. Kraft, Markus |
| author_sort | Zhou, Xiaochi |
| collection | NTU |
| description | Digital twins, Industry 4.0 and Industrial Internet of Things are becoming ever more important in the process industry. The Semantic Web, linked data, knowledge graphs and web services/agents are key technologies for implementing the above concepts. In this paper, we present a comprehensive semantic agent composition framework. It enables automatic agent discovery and composition to generate cross-domain applications. This framework is based on a light-weight agent ontology, OntoAgent, which is an adaptation of the Minimal Service Model (MSM) ontology. The MSM ontology was extended with grounding components to support the execution of an agent while keeping the compatibility with other existing web service description standards and extensibility. We illustrate how the comprehensive agent composition framework can be integrated into the J-Park Simulator (JPS) knowledge graph, for the automatic creation of a composite agent that simulates the dispersion of the emissions of a power plant within a selected spatial area. |
| first_indexed | 2025-02-19T03:50:23Z |
| format | Journal Article |
| id | ntu-10356/152235 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2025-02-19T03:50:23Z |
| publishDate | 2021 |
| record_format | dspace |
| spelling | ntu-10356/1522352023-12-29T06:54:24Z An agent composition framework for the J-Park simulator - a knowledge graph for the process industry Zhou, Xiaochi Eibeck, Andreas Lim, Mei Qi Krdzavac, Nenad B. Kraft, Markus School of Chemical and Biomedical Engineering Cambridge Centre for Advanced Research and Education in Singapore (CARES) Engineering::Chemical engineering Semantic Web Semantic Web Service Composition Digital twins, Industry 4.0 and Industrial Internet of Things are becoming ever more important in the process industry. The Semantic Web, linked data, knowledge graphs and web services/agents are key technologies for implementing the above concepts. In this paper, we present a comprehensive semantic agent composition framework. It enables automatic agent discovery and composition to generate cross-domain applications. This framework is based on a light-weight agent ontology, OntoAgent, which is an adaptation of the Minimal Service Model (MSM) ontology. The MSM ontology was extended with grounding components to support the execution of an agent while keeping the compatibility with other existing web service description standards and extensibility. We illustrate how the comprehensive agent composition framework can be integrated into the J-Park Simulator (JPS) knowledge graph, for the automatic creation of a composite agent that simulates the dispersion of the emissions of a power plant within a selected spatial area. National Research Foundation (NRF) Accepted version This project is supported by the National Research Foundation (NRF), Prime Minister’s Office, Singapore under its Campus for Research Excellence and Technological Enterprise (CREATE) programme. Markus Kraft acknowledges the support of the Alexander von Humboldt foundation. 2021-07-23T06:42:57Z 2021-07-23T06:42:57Z 2019 Journal Article Zhou, X., Eibeck, A., Lim, M. Q., Krdzavac, N. B. & Kraft, M. (2019). An agent composition framework for the J-Park simulator - a knowledge graph for the process industry. Computers and Chemical Engineering, 130, 106577-. https://dx.doi.org/10.1016/j.compchemeng.2019.106577 0098-1354 https://hdl.handle.net/10356/152235 10.1016/j.compchemeng.2019.106577 2-s2.0-85072558187 130 106577 en Computers and Chemical Engineering © 2019 Elsevier Ltd. All rights reserved. This paper was published in Computers and Chemical Engineering and is made available with permission of Elsevier Ltd. application/pdf |
| spellingShingle | Engineering::Chemical engineering Semantic Web Semantic Web Service Composition Zhou, Xiaochi Eibeck, Andreas Lim, Mei Qi Krdzavac, Nenad B. Kraft, Markus An agent composition framework for the J-Park simulator - a knowledge graph for the process industry |
| title | An agent composition framework for the J-Park simulator - a knowledge graph for the process industry |
| title_full | An agent composition framework for the J-Park simulator - a knowledge graph for the process industry |
| title_fullStr | An agent composition framework for the J-Park simulator - a knowledge graph for the process industry |
| title_full_unstemmed | An agent composition framework for the J-Park simulator - a knowledge graph for the process industry |
| title_short | An agent composition framework for the J-Park simulator - a knowledge graph for the process industry |
| title_sort | agent composition framework for the j park simulator a knowledge graph for the process industry |
| topic | Engineering::Chemical engineering Semantic Web Semantic Web Service Composition |
| url | https://hdl.handle.net/10356/152235 |
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