Ontology-Based Access to World Cup Data through Virtual Knowledge Graphs
Resumo
Este artigo apresenta uma arquitetura de virtualização semântica de dados da Copa do Mundo FIFA (1930–2026), combinando a Ontocup, ontologia alinhada à Basic Formal Ontology, com mapeamentos na sintaxe nativa do Ontop (equivalente ao R2RML) para expor uma base PostgreSQL como um Grafo de Conhecimento Virtual consultável via SPARQL, sem materialização completa em RDF. São apresentadas consultas SPARQL com seus equivalentes SQL, verificando sua equivalência e reportando os tempos de execução. Os resultados indicam que a camada ontológica reduz a dependência entre as consultas e o esquema físico e favorece extensões futuras Text-to-SPARQL baseadas em modelos de linguagem de grande porte.Referências
D’Abramo, J., Zugarini, A., and Torroni, P. (2025). Investigating large language models for text-to-SPARQL generation. In Proceedings of the 4th International Workshop on Knowledge-Augmented Methods for Natural Language Processing, pages 66–80, Albuquerque, New Mexico, USA. Association for Computational Linguistics.
Gruber, T. R. (1993). A translation approach to portable ontology specifications. Knowledge Acquisition, 5(2):199–220.
Hogan, A., Blomqvist, E., Cochez, M., et al. (2021). Knowledge graphs. ACM Computing Surveys, 54(4):1–37.
Poggi, A., Lembo, D., Calvanese, D., De Giacomo, G., Lenzerini, M., and Rosati, R. (2008). Linking data to ontologies. In Journal on Data Semantics X, pages 133–173. Springer.
Studer, R., Benjamins, V. R., and Fensel, D. (1998). Knowledge engineering: Principles and methods. Data and Knowledge Engineering, 25(1):161–197.
W3C (2012). R2rml: Rdb to rdf mapping language. W3C Recommendation.
W3C (2013). Sparql 1.1 query language. W3C Recommendation.
W3C (2014). Rdf 1.1 concepts and abstract syntax. W3C Recommendation.
Xiao, G. et al. (2019). Virtual knowledge graphs: An overview of systems and use cases. Data Intelligence, 1(3):201–223.
Xiao, G., Lanti, D., Kontchakov, R., et al. (2020). The virtual knowledge graph system ontop. In International Semantic Web Conference. Springer.
Zhu, X., Li, Q., Cui, L., and Liu, Y. (2024). Large language model enhanced text-to-SQL generation: A survey.
Gruber, T. R. (1993). A translation approach to portable ontology specifications. Knowledge Acquisition, 5(2):199–220.
Hogan, A., Blomqvist, E., Cochez, M., et al. (2021). Knowledge graphs. ACM Computing Surveys, 54(4):1–37.
Poggi, A., Lembo, D., Calvanese, D., De Giacomo, G., Lenzerini, M., and Rosati, R. (2008). Linking data to ontologies. In Journal on Data Semantics X, pages 133–173. Springer.
Studer, R., Benjamins, V. R., and Fensel, D. (1998). Knowledge engineering: Principles and methods. Data and Knowledge Engineering, 25(1):161–197.
W3C (2012). R2rml: Rdb to rdf mapping language. W3C Recommendation.
W3C (2013). Sparql 1.1 query language. W3C Recommendation.
W3C (2014). Rdf 1.1 concepts and abstract syntax. W3C Recommendation.
Xiao, G. et al. (2019). Virtual knowledge graphs: An overview of systems and use cases. Data Intelligence, 1(3):201–223.
Xiao, G., Lanti, D., Kontchakov, R., et al. (2020). The virtual knowledge graph system ontop. In International Semantic Web Conference. Springer.
Zhu, X., Li, Q., Cui, L., and Liu, Y. (2024). Large language model enhanced text-to-SQL generation: A survey.
Publicado
23/09/2026
Como Citar
NASCIMENTO, Lívia Cristina Silva do; MOOS, Rafaela; COUTO, João; PEREIRA, Renata I. S..
Ontology-Based Access to World Cup Data through Virtual Knowledge Graphs. In: ESCOLA REGIONAL DE COMPUTAÇÃO BAHIA, ALAGOAS E SERGIPE (ERBASE), 26. , 2026, Maragogi/AL.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2026
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p. 326-335.
DOI: https://doi.org/10.5753/erbase.2026.32244.
