Journals / International Journal of Informatics and Applied Mathematics / 2026 / Volume: 8 Issue: 2

Semantic Integration of Smart Grid Business Processes Using Knowledge Graphs

Bouhaouche Ibtissem(Guelma university)
Pages
—
Publication Date
2026-01-15
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

As a result, the framework supports more intelligent BP integration and collaboration, and strengthens the overall BP management life cycle in SG systems.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The widespread rollout of Smart Grid (SG) technologies calls for advanced approaches to support the integration and coordination of underlying Business Processes (BPs).
📊
Key Findings & Data: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.
💡
Conclusion & Impact:As a result, the framework supports more intelligent BP integration and collaboration, and strengthens the overall BP management life cycle in SG systems.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Smart Grid (SG) · Business process (BP) · Business Pro- cesses integration

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.

🔖

Cite This Article

Ibtissem, B., Khebızı, A. (2026). Semantic Integration of Smart Grid Business Processes Using Knowledge Graphs. International Journal of Informatics and Applied Mathematics, Volume: 8 Issue: 2. https://doi.org/10.53508/ijiam.1857835

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (37)

  1. References Bonitasoft. (2009). Bonita BPM. Retrieved from https://www.bonitasoft.com
  2. 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
  3. Smart Grid Architecture Overview. (2021). In Smart Grid and Enabling Technologies (pp. 1–43). doi:10.1002/9781119422464.ch1
  4. 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
  5. 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
  6. 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
  7. Macedo, V., Thurler, L., Dias, E., & Cavalcanti, M. (12 2023). Knowledge graph: A strategy for knowledge management? doi:10.56238/sevened2023.006-041
  8. al., C. S. et. (01 2018). Knowledge Graph Modeling for Semantic Integration of Energy Services. 732–735. doi:10.1109/BigComp.2018.00138
  9. 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
  10. Formalisms for EAI: A Survey of Methodologies. (2023). doi:10.33140/jrar.04.01.03
  11. 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
  12. 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
  13. al., B. S. et. (07 2022). Automated Process Knowledge Graph Construction from BPMN Models. doi:10.1007/978-3-031-12423-5_3
  14. 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
  15. 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
  16. 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
  17. 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
  18. 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
  19. 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
  20. 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
  21. Sarica, S., & Luo, J. (07 2021). Design Knowledge Representation with Technology Semantic Network. 1. doi:10.1017/pds.2021.104
  22. 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
  23. 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
  24. 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.
  25. 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
  26. 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
  27. al., A. M. et. (11 2017). Business Process Integration: How to Achieve Interoperability Through Process Pattern.
  28. Morrison, E., Menzies, A., Koliadis, G., & Ghose, A. (01 2009). Business Process Integration: Method and Analysis. Faculty of Informatics - Papers, 96.
  29. al., N. C. et. (2015). Bonita BPM: an innovative BPM-based application development platform to build engaging, user-oriented business applications.
  30. Performance of Graph Database Management Systems as route planning solutions for different data and usage characteristics. (2023). doi:10.48550/arxiv.2306.07084
  31. Ćatović, A., Buzađija, N., & Lemeš, S. (2022). Microservice development using RabbitMQ message broker. Science, Engineering and Technology. doi:10.54327/set2022/v2.i1.19
  32. 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
  33. 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
  34. 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
  35. 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
  36. 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
  37. 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