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ONTOGuide: A Domain Ontology for the Retrieval and Publication of Online Educational Resources

Abstract

In today's digital landscape, the exponential growth of information on the web has led to challenges in its organization and management. Often, resources published on the web lack proper structure or appropriate descriptions, thus making it difficult to establish connections with similar resources—a critical issue when searching for educational materials. In such searches, the need for clear, reliable, and immediately available information takes precedence. There are strategies to tackle this problem, the use of ontologies stands out as a compelling solution because they offer a well-defined, lucid, and precise structure within specific domains. Consequently, this study focuses on crafting a domain-specific ontology that furnishes the required knowledge for publishing and retrieving educational resources from the web. We follow the methodology outlined in "Ontology Development 101: A Guide to Creating Your First Ontology" to design it. The outcome is a domain ontology applicable from two distinct perspectives: an academic standpoint, catering to those who seek to understand the underlying concepts, properties, and relationships involved in resource publication and retrieval; and an industrial one, serving as a support tool for companies or institutions aiming to navigate the process of publishing and retrieving resources to improve the management of their knowledge bases.

Keywords

ontology, open educational resources, educational resources, protégé tool

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References

  1. L. J. Hernández González, Implementación de un prototipo de un sistema de recuperación de información que utilice ontologías para la expansión de consultas, Master Thesis, Tecnológico Nacional de México, Tamaulipas, 2016.
  2. Domo, Data Never Sleeps 8.0 Infographic, 2020. https://www.domo.com/learn/data-never-sleeps-8
  3. J. F. Herrera Cubides, P. A. Gaona García, C. E. Montenegro Marín, Enriquecimiento de recursos educativos: Un enfoque aplicado a la web semántica y datos abiertos, Universidad Distrital Francisco José de Caldas.
  4. D. M. Cataño Peralta, Propuesta Metodológica Para La Publicación De Recursos Digitales Educativos Basado En Linked Open Data. Caso De Estudio: Universidad Distrital Francisco José De Caldas, Grade Thesis, Universidad Distrital Francisco José de Caldas, Bogotá D. C., 2019. https://repository.udistrital.edu.co/handle/11349/16328
  5. J. F. Herrera-cubides, “Linked Data: qué sucede con la heterogeneidad y la interoperabilidad,” Revista Scientia et Technica, vol. 23, no. 2, pp. 230-240, 2018.
  6. N. F. Noy, D. L. McGuinness, Ontology Development 101: A Guide to Creating Your First Ontology, 2001.
  7. M. A. Medina et al., Onto4AIR2: a simple ontology to represent theses from open repositories as products of academic collaboration, 2021. https://www.semantic-web-journal.net/system/files/swj2671.pdf
  8. Gobierno del Estado de Sao Paulo and Gobierno del Reino Unido, Vocabularios y Ontologías | Guía de Web Semántica, 2023. https://ceweb.br/guias/web-semantica/es/introducao/
  9. C. Limongelli, M. Lombardi, A. Marani, D. Taibi, “Enrichment of the Dataset of Joint Educational Entities with the Web of Data,” in IEEE 17th International Conference on Advanced Learning Technologies, 2017, pp. 528–529. https://doi.org/10.1109/ICALT.2017.13
  10. E. Daga, M. D’Aquin, A. Adamou, S. Brown, “The Open University Linked Data - data.open.ac.uk,” Semantic Web, vol. 7, no. 2, pp. 183-191, 2016. https://doi.org/10.3233/SW-150182
  11. S. M. Rashid, D. L. McGuinness, “Creating and using an education standards ontology to improve education,” in CEUR Workshop Proceedings, 2018. https://ceur-ws.org/Vol-2182/paper_7.pdf
  12. E. Ilkou et al., “EduCOR: An Educational and Career-Oriented Recommendation Ontology,” Lecture Notes in Computer Science, vol. 12922, pp. 546-562, 2021. https://doi.org/10.1007/978-3-030-88361-4_32
  13. O. Palombi, F. Jouanot, N. Nziengam, B. Omidvar-Tehrani, M. C. Rousset, A. Sanchez, “OntoSIDES: Ontology-based student progress monitoring on the national evaluation system of French Medical Schools,” Artificial Intelligence in Medicine, vol. 96, pp. 59-67, 2019. https://doi.org/10.1016/j.artmed.2019.03.006
  14. R. Ahmedouamer, A. Hammache, “Ontology-Based Information Retrieval for e-Learning of Computer Science,” in International Conference on Machine and Web Intelligence, Algeria, 2010, pp. 250-257.
  15. J. Gomes Jr, E. Barrere, E. Rocha Soares, J. Souza, “Framework for knowledge discovery in educational video repositories,” Computing and Informatics, vol. 38, pp. 1375-1402, 2019.
  16. A. Romero-Pelaez, V. Segarra-Faggioni, P. P. Alarcon, “Exploring the provenance and accuracy as metadata quality metrics in assessment resources of OCW repositories,” in ACM International Conference Proceeding Series, 2018, pp. 292-296. https://doi.org/10.1145/3290511.3290540
  17. K. El Guemmat. S. Ouahabi, “A semantic distances-based approach for a deeply indexing of learning objects,” International Journal of Emerging Technologies in Learning, vol. 14, no. 6, pp. 27-40, 2019. https://doi.org/10.3991/ijet.v14i06.9738
  18. M. Fernández, A. Gómez-Pérez, N. Jurista, “METHONTOLOGY: From ontologica art towards ontological engineering workshop on Ontological Engineering,” in Spring Symposium Series, 1997. https://aaai.org/papers/0005-SS97-06-005-methontology-from-ontological-art-towards-ontological-engineering/
  19. C. Tautz, C. Gresse von Wangenheim, REFSENO: A representation formalism for software engineering ontologies, 1998.
  20. D. Jones, T. Bench-Capon, P. Visser, “Methodologies for Ontology Development,” in 15th IFIP World Computer Congress, 2007. https://api.semanticscholar.org/CorpusID:8263022
  21. J. Futrelle, “Harvesting RDF triples,” in Lecture Notes in Computer Science, 2006. https://doi.org/10.1007/11890850_8
  22. M. Horridge, R. S. Gonçalves, C. I. Nyulas, T. Tudorache, M. A. Musen, “WebProtégé: A cloud-based ontology editor,” in The Web Conference 2019 - Companion of the World Wide Web Conference, 2019. https://doi.org/10.1145/3308560.3317707
  23. Y. Chen, M. M. Kokar, J. J. Moskal, “SPARQL Query Generator (SQG),” Journal on Data Semantics, vol. 10, no. 3-4, pp. 1-15, 2021.

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