Research Article
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Year 2026, Volume: 8 Issue: 2, 70 - 87, 15.01.2026
https://doi.org/10.53508/ijiam.1857835
https://izlik.org/JA46HM56RP

Abstract

References

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  • Afifi, C., & Khebizi, A. (01 2022). A Road-map for Mining Business Process Models via Artificial Intelligence Techniques. Int. Journal of IAM, 5. doi:10.53508/ijiam.1036234
  • Smart Grid Architecture Overview. (2021). In Smart Grid and Enabling Technologies (pp. 1–43). doi:10.1002/9781119422464.ch1
  • al., D. H. et. (04 2017). Big Data management in smart grid: concepts, requirements and implementation. Jour. of Big Data, 4. doi:10.1186/s40537-017-0070-y
  • Dumas, M., Rosa, M. L., Mendling, J., & Reijers, H. A. (2013). Fundamentals of Business Process Management. Retrieved from https://books.google.fr/books?id=USVEAAAAQBAJ
  • Arnautovic, E., Svetinovic, D., & Diabat, A. (07 2012). Business interactions modeling for systems of systems engineering: Smart grid example. 107–112. doi:10.1109/SYSoSE.2012.6384135
  • Macedo, V., Thurler, L., Dias, E., & Cavalcanti, M. (12 2023). Knowledge graph: A strategy for knowledge management? doi:10.56238/sevened2023.006-041
  • al., C. S. et. (01 2018). Knowledge Graph Modeling for Semantic Integration of Energy Services. 732–735. doi:10.1109/BigComp.2018.00138
  • Chesang’, A. (n.d.). The Effectiveness of Enterprise Resource Planning Systems in Knowledge Management. Jour. of Information and Knowledge Management. doi:10.47941/ejikm.2133
  • Formalisms for EAI: A Survey of Methodologies. (2023). doi:10.33140/jrar.04.01.03
  • al., O. A. et. (2020). 3. Research Trends in Enterprise Service Bus (ESB) Applications: A Systematic Mapping Study. IEEE Access. doi:10.1109/ACCESS.2020.2972195
  • Kumara, I., van den Heuvel, W.-J., & Tamburri, D. A. (2021). QSOC: Quantum Service-Oriented Computing. doi:10.1007/978-3-030-87568-8_3
  • al., B. S. et. (07 2022). Automated Process Knowledge Graph Construction from BPMN Models. doi:10.1007/978-3-031-12423-5_3
  • al., M. C. et. (2019). Model-Driven Context Configuration in BPM Systems: An Approach Based on Knowledge Graphs. Inter. Workshop on Bibliometric-Enhanced Information Retrieval. Retrieved from https://api.semanticscholar.org/CorpusID:202639709
  • al., A. F. et. (2020). An Inferential Knowledge Model for the Digitalisation and Automation of Business Process Analysis. Wirtschaftsinformatik. Retrieved from https://api.semanticscholar.org/CorpusID:215994908
  • al., A. F. et. (2023). Knowledge Graph-Based Explainable Artificial Intelligence for Business Process Analysis. Int. J. Semantic Comput., 17, 173–197. Retrieved from https://api.semanticscholar.org/CorpusID:257001891
  • al., M. S. J. et. (2023). Adoption of knowledge-graph best development practices for scalable and optimized manufacturing processes. MethodsX, 10, 102124. doi:10.1016/j.mex.2023.102124
  • al., K. F. et. (10 2023). On the Representation of Dynamic BPMN Process Executions in Knowledge Graphs. doi:10.1007/978-3-031-47745-4_8
  • Popadić, D., Iglesias, E., Sakor, A., Janev, V., & Vidal, M.-E. (04 2023). Toward a Solution for an Energy Knowledge Graph. doi:10.1007/978-981-19-7126-6_1
  • al., S. C. et. (2018). Designing an integrated knowledge graph for smart energy services. The Journal of Supercomputing, 76, 8058–8085. Retrieved from https://api.semanticscholar.org/CorpusID:53099856
  • Sarica, S., & Luo, J. (07 2021). Design Knowledge Representation with Technology Semantic Network. 1. doi:10.1017/pds.2021.104
  • al., C. C. et. (2022). Less Data, More Knowledge: Building Next Generation Semantic Communication Networks. ArXiv, abs/2211.14343. Retrieved from https://api.semanticscholar.org/CorpusID:254043722
  • al., S. A. et. (04 2017). Towards ontology-based network model management and data integration for smart grids. 1–6. doi:10.1109/MSCPES.2017.8064530
  • al., K. H. J. et. (2020). A comprehensive review of practical issues for interoperability using the CIM model in smart grids. Energies, 13(6), 1435.
  • al., L. W. et. (11 2022). Application of knowledge graph in smart grid fault diagnosis. Applied Mathematics and Nonlinear Sciences, 8. doi:10.2478/amns.2021.2.00258
  • Ma, L., Dou, C., & Hao, T. (04 2023). Grid data asset relationship and intelligent classification integrating knowledge graph and Internet of Things. Applied Mathematics and Nonlinear Sciences, 9. doi:10.2478/amns.2023.1.00059
  • al., A. M. et. (11 2017). Business Process Integration: How to Achieve Interoperability Through Process Pattern.
  • Morrison, E., Menzies, A., Koliadis, G., & Ghose, A. (01 2009). Business Process Integration: Method and Analysis. Faculty of Informatics - Papers, 96.
  • al., N. C. et. (2015). Bonita BPM: an innovative BPM-based application development platform to build engaging, user-oriented business applications.
  • Performance of Graph Database Management Systems as route planning solutions for different data and usage characteristics. (2023). doi:10.48550/arxiv.2306.07084
  • Ćatović, A., Buzađija, N., & Lemeš, S. (2022). Microservice development using RabbitMQ message broker. Science, Engineering and Technology. doi:10.54327/set2022/v2.i1.19
  • Jagannathan, V. (2016). A Context-Aware Approach for Automation of End-User Elements in the Smart Grid (Doctoral dissertation, University of California, Irvine). Retrieved from https://escholarship.org/uc/item/8rw1021w
  • Silva, N. S. e., Castro, R., & Ferrão, P. (2025). Smart Grids in the Context of Smart Cities: A Literature Review and Gap Analysis. Energies, 18(5), 1186. doi:10.3390/en18051186
  • Suri, K., Gaaloul, W., Cuccuru, A., & Gerard, S. (2018). Semantic Framework for Energy-Aware Resource Management of IoT in Business Processes. Int. J. Syst. Serv. -Oriented Eng., 8(1), 21–43. doi:10.4018/IJSSOE.2018010102
  • Diamantini, C., Mircoli, A., Potena, D., & Storti, E. (2023). Process-aware IIoT Knowledge Graph: A semantic model for Industrial IoT integration and analytics. Future Generation Computer Systems, 139, 224–238. doi:10.1016/j.future.2022.10.003
  • Kräuter, T., Rutle, A., König, H., & Lamo, Y. (2024). A higher-order transformation approach to the formalization and analysis of BPMN using graph transformation systems. Logical Methods in Computer Science, 20, Issue 4. doi:10.46298/lmcs-20(4:4)2024
  • Kirikkayis, Y., Winter, M., & Reichert, M. (2024). A User Study on Modeling IoT-Aware Processes with BPMN 2.0. Information, 15(4). doi:10.3390/info15040229

Semantic Integration of Smart Grid Business Processes Using Knowledge Graphs

Year 2026, Volume: 8 Issue: 2, 70 - 87, 15.01.2026
https://doi.org/10.53508/ijiam.1857835
https://izlik.org/JA46HM56RP

Abstract

The widespread rollout of Smart Grid (SG) technologies calls for advanced approaches to support the integration and coordination of underlying Business Processes (BPs). Within SG ecosystems, numerous stakeholders work together toward common objectives, while each one controls its own resources, operates under particular constraints, and follows specific business rules. This makes the design of a unified conceptual framework that enables BP integration and collaboration, while remaining aligned with shared goals, a complex and multifaceted challenge.
This paper tackles the issue of BP integration in SG environments by proposing a new paradigm that combines traditional BPMN models with Knowledge Graph (KG) representations. Unlike conventional methods, the proposed framework exploits the semantic depth and expressive capabilities of KGs to enrich and interconnect BP specifications, thereby enabling adaptive and context-aware business processes. As a result, the framework supports more intelligent BP integration and collaboration, and strengthens the overall BP management life cycle in SG systems.

References

  • References Bonitasoft. (2009). Bonita BPM. Retrieved from https://www.bonitasoft.com
  • Afifi, C., & Khebizi, A. (01 2022). A Road-map for Mining Business Process Models via Artificial Intelligence Techniques. Int. Journal of IAM, 5. doi:10.53508/ijiam.1036234
  • Smart Grid Architecture Overview. (2021). In Smart Grid and Enabling Technologies (pp. 1–43). doi:10.1002/9781119422464.ch1
  • al., D. H. et. (04 2017). Big Data management in smart grid: concepts, requirements and implementation. Jour. of Big Data, 4. doi:10.1186/s40537-017-0070-y
  • Dumas, M., Rosa, M. L., Mendling, J., & Reijers, H. A. (2013). Fundamentals of Business Process Management. Retrieved from https://books.google.fr/books?id=USVEAAAAQBAJ
  • Arnautovic, E., Svetinovic, D., & Diabat, A. (07 2012). Business interactions modeling for systems of systems engineering: Smart grid example. 107–112. doi:10.1109/SYSoSE.2012.6384135
  • Macedo, V., Thurler, L., Dias, E., & Cavalcanti, M. (12 2023). Knowledge graph: A strategy for knowledge management? doi:10.56238/sevened2023.006-041
  • al., C. S. et. (01 2018). Knowledge Graph Modeling for Semantic Integration of Energy Services. 732–735. doi:10.1109/BigComp.2018.00138
  • Chesang’, A. (n.d.). The Effectiveness of Enterprise Resource Planning Systems in Knowledge Management. Jour. of Information and Knowledge Management. doi:10.47941/ejikm.2133
  • Formalisms for EAI: A Survey of Methodologies. (2023). doi:10.33140/jrar.04.01.03
  • al., O. A. et. (2020). 3. Research Trends in Enterprise Service Bus (ESB) Applications: A Systematic Mapping Study. IEEE Access. doi:10.1109/ACCESS.2020.2972195
  • Kumara, I., van den Heuvel, W.-J., & Tamburri, D. A. (2021). QSOC: Quantum Service-Oriented Computing. doi:10.1007/978-3-030-87568-8_3
  • al., B. S. et. (07 2022). Automated Process Knowledge Graph Construction from BPMN Models. doi:10.1007/978-3-031-12423-5_3
  • al., M. C. et. (2019). Model-Driven Context Configuration in BPM Systems: An Approach Based on Knowledge Graphs. Inter. Workshop on Bibliometric-Enhanced Information Retrieval. Retrieved from https://api.semanticscholar.org/CorpusID:202639709
  • al., A. F. et. (2020). An Inferential Knowledge Model for the Digitalisation and Automation of Business Process Analysis. Wirtschaftsinformatik. Retrieved from https://api.semanticscholar.org/CorpusID:215994908
  • al., A. F. et. (2023). Knowledge Graph-Based Explainable Artificial Intelligence for Business Process Analysis. Int. J. Semantic Comput., 17, 173–197. Retrieved from https://api.semanticscholar.org/CorpusID:257001891
  • al., M. S. J. et. (2023). Adoption of knowledge-graph best development practices for scalable and optimized manufacturing processes. MethodsX, 10, 102124. doi:10.1016/j.mex.2023.102124
  • al., K. F. et. (10 2023). On the Representation of Dynamic BPMN Process Executions in Knowledge Graphs. doi:10.1007/978-3-031-47745-4_8
  • Popadić, D., Iglesias, E., Sakor, A., Janev, V., & Vidal, M.-E. (04 2023). Toward a Solution for an Energy Knowledge Graph. doi:10.1007/978-981-19-7126-6_1
  • al., S. C. et. (2018). Designing an integrated knowledge graph for smart energy services. The Journal of Supercomputing, 76, 8058–8085. Retrieved from https://api.semanticscholar.org/CorpusID:53099856
  • Sarica, S., & Luo, J. (07 2021). Design Knowledge Representation with Technology Semantic Network. 1. doi:10.1017/pds.2021.104
  • al., C. C. et. (2022). Less Data, More Knowledge: Building Next Generation Semantic Communication Networks. ArXiv, abs/2211.14343. Retrieved from https://api.semanticscholar.org/CorpusID:254043722
  • al., S. A. et. (04 2017). Towards ontology-based network model management and data integration for smart grids. 1–6. doi:10.1109/MSCPES.2017.8064530
  • al., K. H. J. et. (2020). A comprehensive review of practical issues for interoperability using the CIM model in smart grids. Energies, 13(6), 1435.
  • al., L. W. et. (11 2022). Application of knowledge graph in smart grid fault diagnosis. Applied Mathematics and Nonlinear Sciences, 8. doi:10.2478/amns.2021.2.00258
  • Ma, L., Dou, C., & Hao, T. (04 2023). Grid data asset relationship and intelligent classification integrating knowledge graph and Internet of Things. Applied Mathematics and Nonlinear Sciences, 9. doi:10.2478/amns.2023.1.00059
  • al., A. M. et. (11 2017). Business Process Integration: How to Achieve Interoperability Through Process Pattern.
  • Morrison, E., Menzies, A., Koliadis, G., & Ghose, A. (01 2009). Business Process Integration: Method and Analysis. Faculty of Informatics - Papers, 96.
  • al., N. C. et. (2015). Bonita BPM: an innovative BPM-based application development platform to build engaging, user-oriented business applications.
  • Performance of Graph Database Management Systems as route planning solutions for different data and usage characteristics. (2023). doi:10.48550/arxiv.2306.07084
  • Ćatović, A., Buzađija, N., & Lemeš, S. (2022). Microservice development using RabbitMQ message broker. Science, Engineering and Technology. doi:10.54327/set2022/v2.i1.19
  • Jagannathan, V. (2016). A Context-Aware Approach for Automation of End-User Elements in the Smart Grid (Doctoral dissertation, University of California, Irvine). Retrieved from https://escholarship.org/uc/item/8rw1021w
  • Silva, N. S. e., Castro, R., & Ferrão, P. (2025). Smart Grids in the Context of Smart Cities: A Literature Review and Gap Analysis. Energies, 18(5), 1186. doi:10.3390/en18051186
  • Suri, K., Gaaloul, W., Cuccuru, A., & Gerard, S. (2018). Semantic Framework for Energy-Aware Resource Management of IoT in Business Processes. Int. J. Syst. Serv. -Oriented Eng., 8(1), 21–43. doi:10.4018/IJSSOE.2018010102
  • Diamantini, C., Mircoli, A., Potena, D., & Storti, E. (2023). Process-aware IIoT Knowledge Graph: A semantic model for Industrial IoT integration and analytics. Future Generation Computer Systems, 139, 224–238. doi:10.1016/j.future.2022.10.003
  • Kräuter, T., Rutle, A., König, H., & Lamo, Y. (2024). A higher-order transformation approach to the formalization and analysis of BPMN using graph transformation systems. Logical Methods in Computer Science, 20, Issue 4. doi:10.46298/lmcs-20(4:4)2024
  • Kirikkayis, Y., Winter, M., & Reichert, M. (2024). A User Study on Modeling IoT-Aware Processes with BPMN 2.0. Information, 15(4). doi:10.3390/info15040229
There are 37 citations in total.

Details

Primary Language English
Subjects Knowledge Representation and Reasoning, Modelling and Simulation
Journal Section Research Article
Authors

Bouhaouche Ibtissem

Ali Khebızı 0000-0002-5372-8201

Submission Date January 6, 2026
Acceptance Date January 14, 2026
Publication Date January 15, 2026
DOI https://doi.org/10.53508/ijiam.1857835
IZ https://izlik.org/JA46HM56RP
Published in Issue Year 2026 Volume: 8 Issue: 2

Cite

APA Ibtissem, B., & Khebızı, A. (2026). Semantic Integration of Smart Grid Business Processes Using Knowledge Graphs. International Journal of Informatics and Applied Mathematics, 8(2), 70-87. https://doi.org/10.53508/ijiam.1857835
AMA 1.Ibtissem B, Khebızı A. Semantic Integration of Smart Grid Business Processes Using Knowledge Graphs. IJIAM. 2026;8(2):70-87. doi:10.53508/ijiam.1857835
Chicago Ibtissem, Bouhaouche, and Ali Khebızı. 2026. “Semantic Integration of Smart Grid Business Processes Using Knowledge Graphs”. International Journal of Informatics and Applied Mathematics 8 (2): 70-87. https://doi.org/10.53508/ijiam.1857835.
EndNote Ibtissem B, Khebızı A (January 1, 2026) Semantic Integration of Smart Grid Business Processes Using Knowledge Graphs. International Journal of Informatics and Applied Mathematics 8 2 70–87.
IEEE [1]B. Ibtissem and A. Khebızı, “Semantic Integration of Smart Grid Business Processes Using Knowledge Graphs”, IJIAM, vol. 8, no. 2, pp. 70–87, Jan. 2026, doi: 10.53508/ijiam.1857835.
ISNAD Ibtissem, Bouhaouche - Khebızı, Ali. “Semantic Integration of Smart Grid Business Processes Using Knowledge Graphs”. International Journal of Informatics and Applied Mathematics 8/2 (January 1, 2026): 70-87. https://doi.org/10.53508/ijiam.1857835.
JAMA 1.Ibtissem B, Khebızı A. Semantic Integration of Smart Grid Business Processes Using Knowledge Graphs. IJIAM. 2026;8:70–87.
MLA Ibtissem, Bouhaouche, and Ali Khebızı. “Semantic Integration of Smart Grid Business Processes Using Knowledge Graphs”. International Journal of Informatics and Applied Mathematics, vol. 8, no. 2, Jan. 2026, pp. 70-87, doi:10.53508/ijiam.1857835.
Vancouver 1.Bouhaouche Ibtissem, Ali Khebızı. Semantic Integration of Smart Grid Business Processes Using Knowledge Graphs. IJIAM. 2026 Jan. 1;8(2):70-87. doi:10.53508/ijiam.1857835

International Journal of Informatics and Applied Mathematics