@inproceedings{pires-etal-2026-formalizing,
title = "Formalizing the {DATASUS} {RTS}: An Ontological Model for a Resource Description Framework Knowledge Graph",
author = "Pires, Vitor and
Griebler, Dalvan and
Meneguzzi, Felipe",
editor = "Souza, Marlo and
de-Dios-Flores, Iria and
Santos, Diana and
Freitas, Larissa and
Souza, Jackson Wilke da Cruz and
Ribeiro, Eug{\'e}nio",
booktitle = "Proceedings of the 17th International Conference on Computational Processing of {P}ortuguese ({PROPOR} 2026) - Vol. 1",
month = apr,
year = "2026",
address = "Salvador, Brazil",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.propor-1.90/",
pages = "908--916",
ISBN = "979-8-89176-387-6",
abstract = "The Brazilian DataSUS platform provides vast health databases in relational formats that, while operationally efficient, lack the robust representation needed for advanced scientific data management, restricting interoperability. In this paper, we develop a knowledge engineering pipeline using Scenario 2 of the NeOn methodology to extract, process, and transform knowledge from the DataSUS Health Terminology Repository into a formal knowledge graph that adheres to World Wide Web Consortium standards.We illustrate the potential of this formalization by showing how the graph captures the domain{'}s complex relationships.The resulting graph comprises over 1.4 million triples, with approximately 700,000 associations generated solely through logical inference. Our pipeline provides a foundational resource that enables advanced structural and semantic querying in Portuguese."
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%0 Conference Proceedings
%T Formalizing the DATASUS RTS: An Ontological Model for a Resource Description Framework Knowledge Graph
%A Pires, Vitor
%A Griebler, Dalvan
%A Meneguzzi, Felipe
%Y Souza, Marlo
%Y de-Dios-Flores, Iria
%Y Santos, Diana
%Y Freitas, Larissa
%Y Souza, Jackson Wilke da Cruz
%Y Ribeiro, Eugénio
%S Proceedings of the 17th International Conference on Computational Processing of Portuguese (PROPOR 2026) - Vol. 1
%D 2026
%8 April
%I Association for Computational Linguistics
%C Salvador, Brazil
%@ 979-8-89176-387-6
%F pires-etal-2026-formalizing
%X The Brazilian DataSUS platform provides vast health databases in relational formats that, while operationally efficient, lack the robust representation needed for advanced scientific data management, restricting interoperability. In this paper, we develop a knowledge engineering pipeline using Scenario 2 of the NeOn methodology to extract, process, and transform knowledge from the DataSUS Health Terminology Repository into a formal knowledge graph that adheres to World Wide Web Consortium standards.We illustrate the potential of this formalization by showing how the graph captures the domain’s complex relationships.The resulting graph comprises over 1.4 million triples, with approximately 700,000 associations generated solely through logical inference. Our pipeline provides a foundational resource that enables advanced structural and semantic querying in Portuguese.
%U https://aclanthology.org/2026.propor-1.90/
%P 908-916
Markdown (Informal)
[Formalizing the DATASUS RTS: An Ontological Model for a Resource Description Framework Knowledge Graph](https://aclanthology.org/2026.propor-1.90/) (Pires et al., PROPOR 2026)
ACL