Ontology Engineering for Modeling National Student Achievements in Higher Education

Authors

  • Ajeng Rahma Sudarni Universitas Negeri Semarang Author
  • Septian Eko Prasetyo Universitas Negeri Semarang Author
  • Alfian Ardhiansyah Universitas Negeri Semarang Author
  • Mulil Khaira Universitas Negeri Semarang Author

DOI:

https://doi.org/10.15294/edukom.v11i2.28254

Keywords:

Ontology Engineering, Reasoning, Semantic Web, Student Achivement

Abstract

The need for structured and semantically rich data in higher education underscores the role of ontology-based knowledge modeling. This study develops an ontology to represent national-level student achievements, covering key aspects such as institution, achievement field, category, year, level, and student status. Using a formal ontology engineering approach, the ontology was developed in Protégé and encoded in OWL. Evaluation involved technical validation and reasoning tests including class subsumption, consistency checking, instance classification, and rule-based inference to assess logical soundness and semantic correctness. Description Logic (DL) queries were also executed based on competency questions to evaluate the ontology’s ability to support semantic querying. The results demonstrate that the ontology effectively supports knowledge inference and structured data retrieval, offering strong potential for integration within semantic web environments. This provides a foundation for data interoperability and knowledge sharing across educational systems at the national level. Future work includes expanding the ontology to incorporate dynamic achievement updates and linking with external educational data sources.

References

Ashour, G., Al-Dubai, A., Romdhani, I., & Aljohani, N. (2020). An Ontological Model for Courses and Academic Profiles Representation: A case study of King Abdulaziz University. 2020 International Conference Engineering Technologies and Computer Science (EnT), 123–126. https://doi.org/10.1109/EnT48576.2020.00030

Beerkens, M. (2022). An evolution of performance data in higher education governance: a path towards a ‘big data’ era? Quality in Higher Education, 28(1), 29–49. https://doi.org/10.1080/13538322.2021.1951451

Boudia, M., & Bourahla, M. (2022). Formalization of Ontology Conceptualizations Using Model Transformation. International Journal of Information System Modeling and Design, 13(1), 1–21. https://doi.org/10.4018/IJISMD.305229

Cabada, R. Z., López, H. M. C., & Escalante, H. J. (2023). Methods for Data Representation. In Multimodal Affective Computing (pp. 55–65). Springer International Publishing. https://doi.org/10.1007/978-3-031-32542-7_5

Castellanos, A., Tremblay, M., Lukyanenko, R., & Samuel, B. (2020). Basic Classes in Conceptual Modeling: Theory and Practical Guidelines. Journal of the Association for Information Systems, 21, 1001–1044. https://doi.org/10.17705/1jais.00627

Chen, Y., Kokar, M. M., Moskal, J. J., & Suresh, D. (2021). Mapping spectrum consumption models to cognitive radio ontology for automatic inference. Analog Integrated Circuits and Signal Processing, 106(1), 9–21. https://doi.org/10.1007/s10470-017-1095-z

Dwyer, O. P., Chammas, L., Sallinger, E., & Davies, J. (2025). Using ontologies to facilitate healthcare process mining and analysis. Journal of Intelligent Information Systems. https://doi.org/10.1007/s10844-025-00942-8

Espinoza, A., Del-Moral, E., Martínez-Martínez, A., & Alí, N. (2021). A validation & verification driven ontology: An iterative process. Applied Ontology, 16(3), 297–337. https://doi.org/10.3233/AO-210251

Fahad, M., Javid, T., Beenish, H., Siddiqui, A. A., & Ahmed, G. (2021). Extending ONTAgri with Service-Oriented Architecture towards Precision Farming Application. Sustainability, 13(17), 9801. https://doi.org/10.3390/su13179801

Fusco, G., & Aversano, L. (2020). An approach for semantic integration of heterogeneous data sources. PeerJ Computer Science, 6, e254. https://doi.org/10.7717/peerj-cs.254

George Andreas. (2023). Ontology Engineering: Building a Semantic Foundation for Knowledge Representation. International Journal of Swarm Intelligence and Evolutionary Computation, 12(3).

Goldstein, A., Fink, L., & Ravid, G. (2021). A Framework for Evaluating Agricultural Ontologies. Sustainability, 13(11), 6387. https://doi.org/10.3390/su13116387

Hagedorn, T., Bone, M., Kruse, B., Grosse, I., & Blackburn, M. (2020). Knowledge Representation with Ontologies and Semantic Web Technologies to Promote Augmented and Artificial Intelligence in Systems Engineering. INSIGHT, 23(1), 15–20. https://doi.org/10.1002/inst.12279

Hamdana, E. N., & Apriyani, M. E. (2020). ANALISIS IMPLEMENTASI RESTFULL WEB SERVICE MENGGUNAKAN RESOURCE-ORIENTED ARCHITECTURE. Jurnal Informatika Polinema, 6(2), 57–60. https://doi.org/10.33795/jip.v6i2.335

Ilkou, E., Abu-Rasheed, H., Tavakoli, M., Hakimov, S., Kismihók, G., Auer, S., & Nejdl, W. (2021). EduCOR: An Educational and Career-Oriented Recommendation Ontology (pp. 546–562). https://doi.org/10.1007/978-3-030-88361-4_32

Kotis, K. I., Vouros, G. A., & Spiliotopoulos, D. (2020a). Ontology engineering methodologies for the evolution of living and reused ontologies: status, trends, findings and recommendations. The Knowledge Engineering Review, 35, e4. https://doi.org/10.1017/S0269888920000065

Kotis, K. I., Vouros, G. A., & Spiliotopoulos, D. (2020b). Ontology engineering methodologies for the evolution of living and reused ontologies: status, trends, findings and recommendations. The Knowledge Engineering Review, 35, e4. https://doi.org/10.1017/S0269888920000065

Lei, X., Wu, P., Zhu, J., & Wang, J. (2022). Ontology-Based Information Integration: A State-of-the-Art Review in Road Asset Management. Archives of Computational Methods in Engineering, 29(5), 2601–2619. https://doi.org/10.1007/s11831-021-09668-6

Masmoudi, M., Ben Abdallah Ben Lamine, S., Karray, M. H., Archimede, B., & Baazaoui Zghal, H. (2024). Semantic Data Integration and Querying: A Survey and Challenges. ACM Computing Surveys, 56(8), 1–35. https://doi.org/10.1145/3653317

Meghini, C., Bartalesi, V., & Metilli, D. (2021). Representing narratives in digital libraries: The narrative ontology. Semantic Web, 12(2), 241–264. https://doi.org/10.3233/SW-200421

Mohamad Hashim, S. F., Salim, J., Mohd Noah, S. A. M. N., & Wan Mustapha, W. A. (2023). Ontology-Based Traceability System for Halal Status of Flavour. Malaysian Journal of Information and Communication Technology (MyJICT), 65–77. https://doi.org/10.53840/myjict8-2-97

O’Neill, B., & Stapleton, L. (2022). Digital cultural heritage standards: from silo to semantic web. AI & SOCIETY, 37(3), 891–903. https://doi.org/10.1007/s00146-021-01371-1

Reginato, C. C., Salamon, J. S., Nogueira, G. G., Barcellos, M. P., Souza, V. E. S., Monteiro, M. E., & Guizzardi, R. (2022). A goal-oriented framework for ontology reuse. Applied Ontology, 17(3), 365–399. https://doi.org/10.3233/AO-220269

Shi, W., Bao, S., & Tan, D. (2019). FFESSD: An Accurate and Efficient Single-Shot Detector for Target Detection. Applied Sciences, 9(20), 4276. https://doi.org/10.3390/app9204276

Wan, L., Song, J., He, V., Roman, J., Whah, G., Peng, S., Zhang, L., & He, Y. (2021). Development of the International Classification of Diseases Ontology (ICDO) and its application for COVID-19 diagnostic data analysis. BMC Bioinformatics, 22(S6), 508. https://doi.org/10.1186/s12859-021-04402-2

Wu, J. (2024). Integration of higher education student management and pedagogical concepts based on data-based decision making. Applied Mathematics and Nonlinear Sciences, 9(1). https://doi.org/10.2478/amns-2024-0991

Zahila, M. N., Noorhidawati, A., & Yanti Idaya Aspura, M. K. (2021). Content extraction of historical Malay manuscripts based on Event Ontology Framework. Applied Ontology, 16(3), 249–275. https://doi.org/10.3233/AO-210247

Zaitoun, A., Sagi, T., & Hose, K. (2023). Automated Ontology Evaluation: Evaluating Coverage and Correctness using a Domain Corpus. Companion Proceedings of the ACM Web Conference 2023, 1127–1137. https://doi.org/10.1145/3543873.3587617

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Published

2024-12-31

Article ID

28254

How to Cite

Sudarni, A. R., Prasetyo, S. E., Ardhiansyah, A. ., & Khaira, M. (2024). Ontology Engineering for Modeling National Student Achievements in Higher Education. Edu Komputika Journal, 11(2), 126-135. https://doi.org/10.15294/edukom.v11i2.28254