Integração entre SPARQL e Business Intelligence: Um Driver para Visualização de Dados RDF no Metabase
Resumo
A visualização interativa de dados RDF via SPARQL permanece um desafio para ferramentas de Business Intelligence (BI). Este trabalho apresenta o desenvolvimento de um driver para o Metabase, implementado em Clojure, que permite a consulta direta a endpoints SPARQL e a exploração desses dados em modelos tabulares. Diferentemente das ferramentas existentes, baseadas em bibliotecas web e que exigem conhecimento técnico, a proposta integra dados RDF a uma plataforma de BI consolidada. A solução utiliza a estratégia de tabelas de propriedades particionadas por classes, realizando a descoberta automática de metadados e conversão de tipos XSD. Testes realizados em endpoints públicos, como DBpedia e Wikidata, demonstram a viabilidade de criar visualizações de barras, linhas, dispersão e mapas, tanto via consultas nativas quanto de forma visual. Os resultados indicam a viabilidade técnica de visualizar e explorar dados RDF em uma plataforma de BI.
Palavras-chave:
RDF, SPARQL, Metabase, Business Intelligence
Referências
Alpar, P. and Schulz, M. (2016). Self-service business intelligence. Business & Information Systems Engineering, 58:151–155.
Berners-Lee, T., Hendler, J., and Lassila, O. (2001). The semantic web. Scientific American, 284(5):34–43.
Buil-Aranda, C., Hogan, A., Umbrich, J., and Vandenbussche, P.-Y. (2013). Sparql web-querying infrastructure: Ready for action? In Alani, H., Kagal, L., Fokoue, A., Groth, P., Biemann, C., Parreira, J. X., Aroyo, L., Noy, N., Welty, C., and Janowicz, K., editors, The Semantic Web - ISWC 2013, pages 277–293, Berlin, Heidelberg. Springer Berlin Heidelberg.
Cabral, J. V. d. C. H. A. (2025). Driver para visualização de dados RDF via SPARQL no Metabase. Monografia, Universidade Federal do Rio de Janeiro, Rio de Janeiro.
Clark, K. G., Feigenbaum, L., and Torres, E. (2007). Serializing sparql query results in json. W3c working group note, World Wide Web Consortium (W3C).
Katayama, T. (2014). D3sparql: Javascript library for visualization of sparql results. In Semantic Web Applications and Tools for Life Sciences 2014 (SWAT4LS 2014), volume 1320 of CEUR Workshop Proceedings.
Menin, A., Maillot, P., Faron, C., Corby, O., Dal Sasso Freitas, C. M., Gandon, F., and Winckler, M. (2023). LDViz: a tool to assist the multidimensional exploration of SPARQL endpoints. In Web Information Systems and Technologies : 16th International Conference, WEBIST 2020, November 3-5, 2020, and 17th International Conference, WEBIST 2021, October 26-28, 2021, Virtual Events, Revised Selected Papers, volume LNBIP - 469 of LNBIP - Lecture Notes in Business Information Processing, pages 149–173. Springer.
Metabase (2025). Metabase documentation. Available at: [link]. Accessed on: Jul. 8, 2025.
Rajabi, E., Midha, R., and de Souza, J. F. (2023). Constructing a knowledge graph for open government data: the case of nova scotia disease datasets. Journal of Biomedical Semantics, 14(1):4.
Seaborne, A., Clark, K. G., Feigenbaum, L., and Torres, E. (2013). Sparql 1.1 query results json format. W3c recommendation, World Wide Web Consortium (W3C).
Skjæveland, M. G. (2015). Sgvizler: A javascript wrapper for easy visualization of sparql result sets. In Simperl, E., Norton, B., Mladenic, D., Della Valle, E., Fundulaki, I., Passant, A., and Troncy, R., editors, The Semantic Web: ESWC 2012 Satellite Events, pages 361–365, Berlin, Heidelberg. Springer Berlin Heidelberg.
Stear, B. J., Mohseni Ahooyi, T., Simmons, J. A., Kollar, C., Hartman, L., Beigel, K., Lahiri, A., Vasisht, S., Callahan, T. J., Nemarich, C. M., Silverstein, J. C., and Taylor, D. M. (2024). Petagraph: A large-scale unifying knowledge graph framework for integrating biomolecular and biomedical data. Scientific Data, 11(1).
Thellmann, K., Galkin, M., Orlandi, F., and Auer, S. (2015). Linkdaviz - automatic binding of linked data to visualizations. In Arenas, M., Corcho, O., Simperl, E., Strohmaier, M., d’Aquin, M., Srinivas, K., Groth, P., Dumontier, M., Heflin, J., Thirunarayan, K., Thirunarayan, K., and Staab, S., editors, The Semantic Web ISWC 2015, pages 147–162, Cham. Springer International Publishing.
Uschold, M. (2018). Demystifying OWL for the enterprise. Synthesis Lectures on the Semantic Web: Theory and Technology. Morgan & Claypool, San Rafael, CA.
Vandenbussche, P.-Y., Umbrich, J., Matteis, L., Hogan, A., and Buil-Aranda, C. (2017). Sparqles: Monitoring public sparql endpoints. Semant. Web, 8(6):1049–1065.
W3C SPARQL Working Group (2013). Sparql 1.1 protocol. W3c recommendation, World Wide Web Consortium (W3C).
Walker, J., Buijs, O., Ivie, C., and de Koning, J. (2022). How NXP performs event-driven RDF imports to Amazon Neptune using AWS Lambda and SPARQL UPDATE LOAD. Available at: [link]. Accessed on: Jul. 8, 2025.
Wilkinson, K., Sayers, C., Kuno, H. A., and Reynolds, D. (2003). Efficient rdf storage and retrieval in jena2. In Proceedings of the First International Conference on Semantic Web and Databases, SWDB’03, pages 131–150, Aachen, DEU. CEUR-WS.org.
Wood, D., Lanthaler, M., and Cyganiak, R. (2014). Rdf 1.1 concepts and abstract syntax. W3c recommendation, World Wide Web Consortium (W3C).
Yuan, G., Lu, J., Yan, Z., and Wu, S. (2023). A survey on mapping semi-structured data and graph data to relational data. ACM Comput. Surv., 55(10).
Berners-Lee, T., Hendler, J., and Lassila, O. (2001). The semantic web. Scientific American, 284(5):34–43.
Buil-Aranda, C., Hogan, A., Umbrich, J., and Vandenbussche, P.-Y. (2013). Sparql web-querying infrastructure: Ready for action? In Alani, H., Kagal, L., Fokoue, A., Groth, P., Biemann, C., Parreira, J. X., Aroyo, L., Noy, N., Welty, C., and Janowicz, K., editors, The Semantic Web - ISWC 2013, pages 277–293, Berlin, Heidelberg. Springer Berlin Heidelberg.
Cabral, J. V. d. C. H. A. (2025). Driver para visualização de dados RDF via SPARQL no Metabase. Monografia, Universidade Federal do Rio de Janeiro, Rio de Janeiro.
Clark, K. G., Feigenbaum, L., and Torres, E. (2007). Serializing sparql query results in json. W3c working group note, World Wide Web Consortium (W3C).
Katayama, T. (2014). D3sparql: Javascript library for visualization of sparql results. In Semantic Web Applications and Tools for Life Sciences 2014 (SWAT4LS 2014), volume 1320 of CEUR Workshop Proceedings.
Menin, A., Maillot, P., Faron, C., Corby, O., Dal Sasso Freitas, C. M., Gandon, F., and Winckler, M. (2023). LDViz: a tool to assist the multidimensional exploration of SPARQL endpoints. In Web Information Systems and Technologies : 16th International Conference, WEBIST 2020, November 3-5, 2020, and 17th International Conference, WEBIST 2021, October 26-28, 2021, Virtual Events, Revised Selected Papers, volume LNBIP - 469 of LNBIP - Lecture Notes in Business Information Processing, pages 149–173. Springer.
Metabase (2025). Metabase documentation. Available at: [link]. Accessed on: Jul. 8, 2025.
Rajabi, E., Midha, R., and de Souza, J. F. (2023). Constructing a knowledge graph for open government data: the case of nova scotia disease datasets. Journal of Biomedical Semantics, 14(1):4.
Seaborne, A., Clark, K. G., Feigenbaum, L., and Torres, E. (2013). Sparql 1.1 query results json format. W3c recommendation, World Wide Web Consortium (W3C).
Skjæveland, M. G. (2015). Sgvizler: A javascript wrapper for easy visualization of sparql result sets. In Simperl, E., Norton, B., Mladenic, D., Della Valle, E., Fundulaki, I., Passant, A., and Troncy, R., editors, The Semantic Web: ESWC 2012 Satellite Events, pages 361–365, Berlin, Heidelberg. Springer Berlin Heidelberg.
Stear, B. J., Mohseni Ahooyi, T., Simmons, J. A., Kollar, C., Hartman, L., Beigel, K., Lahiri, A., Vasisht, S., Callahan, T. J., Nemarich, C. M., Silverstein, J. C., and Taylor, D. M. (2024). Petagraph: A large-scale unifying knowledge graph framework for integrating biomolecular and biomedical data. Scientific Data, 11(1).
Thellmann, K., Galkin, M., Orlandi, F., and Auer, S. (2015). Linkdaviz - automatic binding of linked data to visualizations. In Arenas, M., Corcho, O., Simperl, E., Strohmaier, M., d’Aquin, M., Srinivas, K., Groth, P., Dumontier, M., Heflin, J., Thirunarayan, K., Thirunarayan, K., and Staab, S., editors, The Semantic Web ISWC 2015, pages 147–162, Cham. Springer International Publishing.
Uschold, M. (2018). Demystifying OWL for the enterprise. Synthesis Lectures on the Semantic Web: Theory and Technology. Morgan & Claypool, San Rafael, CA.
Vandenbussche, P.-Y., Umbrich, J., Matteis, L., Hogan, A., and Buil-Aranda, C. (2017). Sparqles: Monitoring public sparql endpoints. Semant. Web, 8(6):1049–1065.
W3C SPARQL Working Group (2013). Sparql 1.1 protocol. W3c recommendation, World Wide Web Consortium (W3C).
Walker, J., Buijs, O., Ivie, C., and de Koning, J. (2022). How NXP performs event-driven RDF imports to Amazon Neptune using AWS Lambda and SPARQL UPDATE LOAD. Available at: [link]. Accessed on: Jul. 8, 2025.
Wilkinson, K., Sayers, C., Kuno, H. A., and Reynolds, D. (2003). Efficient rdf storage and retrieval in jena2. In Proceedings of the First International Conference on Semantic Web and Databases, SWDB’03, pages 131–150, Aachen, DEU. CEUR-WS.org.
Wood, D., Lanthaler, M., and Cyganiak, R. (2014). Rdf 1.1 concepts and abstract syntax. W3c recommendation, World Wide Web Consortium (W3C).
Yuan, G., Lu, J., Yan, Z., and Wu, S. (2023). A survey on mapping semi-structured data and graph data to relational data. ACM Comput. Surv., 55(10).
Publicado
08/09/2026
Como Citar
CABRAL, José Vitor Hisse; LOPES, Giseli Rabello; PINHEIRO, João Pedro.
Integração entre SPARQL e Business Intelligence: Um Driver para Visualização de Dados RDF no Metabase. In: SIMPÓSIO BRASILEIRO DE BANCO DE DADOS (SBBD), 41. , 2026, São Carlos/SP.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2026
.
p. 728-741.
ISSN 2763-8979.
DOI: https://doi.org/10.5753/sbbd.2026.249314.
