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A Proposal of a Knowledge Graph for Digital Engineering Systems Integration for Operation and Maintenance Activities in Industrial Plants

Published: 23 May 2024 Publication History

Abstract

Context: Over the last years, we have observed Knowledge Graphs (KGs) being used more and more as a tool for representing knowledge, data integration and querying data. Problem: There are many distinguished yet partially-integrated information management systems used to support the life-cycle of Oil and Gas industrial plants. Our approach considers a 3D plants viewer system, a visual navigation system on platforms, and the integrated intelligent search system. However, these systems lack a semantic integration that can guide the user actions over each functionality for a unique asset. Solution: This paper presents the use of KGs to represent and help monitoring and controlling operational and maintenance activities within an Oil and Gas industrial environment. Our approach highlights the challenges and initial work required to establish a fully-integrated management domain, where the execution of the aforementioned activities can easily be managed. SI Theory: This study draws inspiration from Representation Theory, which posits that an information system faithfully mirrors specific phenomena occurring in the physical world. Method: To develop this work, it was necessary to review the literature related to the development of KGs and ontologies. The generated KG was developed using well-established standards like the Industrial Data Ontology (IDO), and the Capital Facilities Information Handover Specification (CFIHOS), complemented with the use of other ontologies. Summary of Results: A prototype of the conceptual KG was implemented, verifying the viability of our approach for data integration. Contributions and Impact in IS area: The resulted graph contains the main terms in compliance with international semantic standards for representing operational and maintenance activities data associated with facilities involved in Oil and Gas production. Finally, the KG resulting from this effort can be further extended through the incorporation of new tools and subdomains in the industrial plants life-cycle.

References

[1]
2007. OntoCAPE—A large-scale ontology for chemical process engineering. Engineering Applications of Artificial Intelligence 20, 2 (2007), 147–161. https://doi.org/10.1016/j.engappai.2006.06.010 Special Issue on Applications of Artificial Intelligence in Process Systems Engineering.
[2]
Piero Andrea Bonatti, Stefan Decker, Axel Polleres, and Valentina Presutti. 2019. Knowledge Graphs: New Directions for Knowledge Representation on the Semantic Web (Dagstuhl Seminar 18371). Dagstuhl Reports 8, 9 (2019), 29–111. https://doi.org/10.4230/DagRep.8.9.29
[3]
B. Brewton. 2023. How Using Knowledge Graphs can Optimize the Oil and Gas Industry. https://www.linkedin.com/pulse/how-using-knowledge-graphs-can-optimize-oil-gas-industry-jon-brewton#
[4]
Mario Bunge. 1977. Treatise on Basic Philosophy: Ontology I: The Furniture of the World. Vol. 3. Springer Dordrecht, D. Reidel Publishing Company, Dordrecht, Holland. https://doi.org/10.1007/978-94-010-9924-0
[5]
Dublin Core Metadata Initiative (DCMI). [n. d.]. Dublin Core. https://www.dublincore.org/resources/glossary/ontology/ Acessado em 4 de dezembro de 2023.
[6]
Antonio De Nicola and Michele Missikoff. 2016. A Lightweight Methodology for Rapid Ontology Engineering. Commun. ACM 59, 3 (feb 2016), 79–86. https://doi.org/10.1145/2818359
[7]
Diarmuid Ryan. 2014. Cartesian Coordinate Ontology. http://diarmuidr3d.github.io/cartCoord/ Accessed on December 4, 2023.
[8]
Lisa Ehrlinger and Wolfram Wöß. 2016. Towards a Definition of Knowledge Graphs.
[9]
M. Fernández-López, A. Gómez-Pérez, and N. Juristo. 1997. METHONTOLOGY: From Ontological Art Towards Ontological Engineering. In Proceedings of the Ontological Engineering AAAI-97 Spring Symposium Series. American Asociation for Artificial Intelligence, Stanford University, EEUU, 33–40. https://oa.upm.es/5484/ Ontology Engineering Group ? OEG.
[10]
Shujun Huang, Yuyan Wang, and Xiang Yu. 2020. Design and Implementation of Oil and Gas Information on Intelligent Search Engine Based on Knowledge Graph. Journal of Physics: Conference Series 1621 (08 2020), 012010. https://doi.org/10.1088/1742-6596/1621/1/012010
[11]
Theories Used in IS Research Wiki group of authors. [n. d.]. Representation Theory. https://is.theorizeit.org/wiki/Representation_Theory Acessado em 24 de novembro de 2023.
[12]
The Alan Turing Institute. 2023. Knowledge graphs. https://www.turing.ac.uk/research/interest-groups/knowledge-graphs#: :text=Knowledge%20graphs%20can%20be%20created, data%20validation%20and%20integration%20mechanisms
[13]
Instituto Brasileiro de Petróleo e Gás 2020. Estado da Arte Sobre Arquiteturas de Sistemas para Integração de Dados. Instituto Brasileiro de Petróleo e Gás. https://doi.org/10.48072/2525-7579.rog.2020.414
[14]
International Association of Oil & Gas Producers. 2021. CFIHOS-Specification-Document. IOJP - CFIHOS. https://www.jip36-cfihos.org/wp-content/uploads/2023/08/v.1.5.1-CFIHOS-Specification-Document-1.docxAccessed on December 10, 2023.
[15]
David Moher, Alessandro Liberati, Jennifer Tetzlaff, Douglas G Altman, and PRISMA Group*. 2009. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Annals of internal medicine 151, 4 (2009), 264–269.
[16]
Charalampos Nikolaou, Egor V. Kostylev, George Konstantinidis, Mark Kaminski, Bernardo Cuenca Grau, and Ian Horrocks. 2019. Foundations of ontology-based data access under bag semantics. Artificial Intelligence 274 (2019), 91–132. https://doi.org/10.1016/j.artint.2019.02.003
[17]
PCA - READI. 2021. PCA Reference Data and Services. POSC Caesar Association (PCA) in a collaboration between the READI Joint Industry Project and the KRAFLA and NOA Oil and Gas. https://rds.posccaesar.orgAccessed on December 4, 2023.
[18]
POSC Caesar Association. 2023. Industrial Data Ontology. POSC Caesar Association (PCA). https://rds.posccaesar.org/WD_IDO.pdfAccessed on December 9, 2023.
[19]
Prof. Paulo Ivson. 2023. Challenges in Computer Graphics and AI for Digital Engineering. Departamento de Informática - PUC-Rio. https://www.youtube.com/live/BXVnlSBTgBc?si=cxmpLysuF2G1_qG6Accessed on December 4, 2023.
[20]
READI JIP. 2021. READI JIP. IOJP. https://readi-jip.orgAccessed on December 4, 2023.
[21]
SAP official site. 2023. SAP-ERP. SAP. https://www.sap.com/brazil/index.htmlAccessed on December 8, 2023.
[22]
Xianming Tang, Zhiqiang Feng, Yitian Xiao, Ming Wang, Tianrui Ye, Yujie Zhou, Jin Meng, Baosen Zhang, and Dongwei Zhang. 2022. Construction and application of an ontology-based domain-specific knowledge graph for petroleum exploration and development. Geoscience Frontiers 14, 5 (2022), 101426. https://doi.org/10.1016/j.gsf.2022.101426
[23]
Panos Vassiliadis. 2009. A Survey of Extract-Transform-Load Technology.International Journal of Data Warehousing and Mining 5 (07 2009), 1–27.
[24]
W3C. 2009. SKOS Simple Knowledge Organization System Reference. World Wide Web Consortium (W3C). https://www.w3.org/TR/skos-reference/Accessed on November 24, 2023.
[25]
W3C. 2014. The Organization Ontology. W3C Recommendation. World Wide Web Consortium (W3C). https://www.w3.org/TR/vocab-org/Accessed on December 4, 2023.
[26]
Yair Wand and Ron Weber. 1988. An Ontological Analysis of some Fundamental Information Systems Concepts. In ICIS 1988 Proceedings (Helsinki, Finland). Association for Information Systems, USA, 461 pages. https://dl.acm.org/doi/proceedings/10.5555/353053
[27]
Yair Wand and Ron Weber. 1989. Information Systems Concepts: An In-depth Analysis: proceedings of the IFIP TC 8/WG 8.1 Working Conference on Information System Concepts: an in-depth analysis Namur, Belgium, 18-20 October, 1989. Elsevier, Belgium, Chapter An ontological evaluation of systems analysis and design methods.
[28]
Y. Wand and R. Weber. 1990. Mario Bunge’s ontology as a formal foundation for information systems concepts. Studies on Mario Bunge’s Treatise (1990), 123 – 149. https://www.scopus.com/inward/record.uri?eid=2-s2.0-0008234485&partnerID=40&md5=4f9a93837a36f46caeec589ede2b649e
[29]
Y. Wand and R. Weber. 1990. An ontological model of an information system. IEEE Transactions on Software Engineering 16, 11 (1990), 1282–1292. https://doi.org/10.1109/32.60316
[30]
Y. Wand and R. Weber. 1993. On the ontological expressiveness of information systems analysis and design grammars. Information Systems Journal 3, 4 (1993), 217–237. https://doi.org/10.1111/j.1365-2575.1993.tb00127.x arXiv:https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1365-2575.1993.tb00127.x
[31]
Yair Wand and Ron Weber. 1995. On the deep structure of information systems. Information Systems Journal 5, 3 (1995), 203–223. https://doi.org/10.1111/j.1365-2575.1995.tb00108.x arXiv:https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1365-2575.1995.tb00108.x
[32]
Guohui Xiao, Linfang Ding, Benjamin Cogrel, and Diego Calvanese. 2019. Virtual Knowledge Graphs: An Overview of Systems and Use Cases. Data Intelligence 1, 3 (2019), 201–223. https://doi.org/10.1162/dint_a_00011

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    SBSI '24: Proceedings of the 20th Brazilian Symposium on Information Systems
    May 2024
    708 pages
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    Published: 23 May 2024

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    Author Tags

    1. Data Integration
    2. Digital Engineering
    3. Industrial Plants
    4. Knowledge Graphs
    5. Ontology
    6. Operation and Maintenance activities

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    SBSI '24
    SBSI '24: XX Brazilian Symposium on Information Systems
    May 20 - 23, 2024
    Juiz de Fora, Brazil

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