Title:	KGAP: an RDF knowledge graph of agricultural commodity prices.
Authors:	SOARES, F. M. PIRES, L. F. CORRÊA, F. E. SANTOS, L. O. B. da S. BRAGHETTO, K. L. MOREIRA, D. de A. DRUCKER, D. P. DELBEM, A. C. B. SARAIVA, A. M.
Affiliation:	FILIPI MIRANDA SOARES, UNIVERSITY OF TWENTE, UNIVERSIDADE DE SÃO PAULO, UNIVERSITY OF MONTPELLIER; LUÍS FERREIRA PIRES, UNIVERSITY OF TWENTE; FERNANDO ELIAS CORRÊA, UNIVERSIDADE DE SÃO PAULO; LUIZ OLAVO BONINO DA SILVA SANTOS, UNIVERSITY OF TWENTE, LEIDEN UNIVERSITY MEDICAL CENTER; KELLY ROSA BRAGHETTO, UNIVERSIDADE DE SÃO PAULO; DILVAN DE ABREU MOREIRA, UNIVERSIDADE DE SÃO PAULO; DEBORA PIGNATARI DRUCKER, CNPTIA; ALEXANDRE CLÁUDIO BOTAZZO DELBEM, UNIVERSIDADE DE SÃO PAULO; ANTONIO MAURO SARAIVA, UNIVERSIDADE DE SÃO PAULO.
Date Issued:	2026
Citation:	Data in Brief, v. 65, 112607, Apr. 2026.
Description:	This article presents the Knowledge Graph for Agricultural Prices (KGAP), which is a knowledge graph (KG) that integrates agricultural commodity prices data from three major Brazilian institutions: Cepea, Conab, and Ipea. The datasets, originally published in heterogeneous formats, were harmonized and converted into RDF/Turtle using the Almes Core metadata schema as the data model. Agricultural products were classified with the Agricultural Product Types Ontology (APTO), and geographic references were aligned with GeoNames identifiers, ensuring semantic consistency and adherence to the FAIR data principles. KGAP is archived on Zenodo and GitHub, and hosted on the Platform Linked Data Nederland (PLDN) with a public SPARQL endpoint. It contains metadata, price observations, product types, and location entities, allowing users to query and compare agricultural prices across institutions, regions, and time periods. The knowledge graph can potentially support applications in agricultural economics, policy analysis, journalism, data science, and machine learning. By explicitly modeling metadata such as reference quantities, KGAP enables semanticallyaware queries that prevent common analytical errors and reveal insights previously obscured by data heterogeneity.
Thesagro:	Economia Agrícola Preço
NAL Thesaurus:	Agricultural economics Agricultural products Prices Time series analysis
Keywords:	Produtos agrícolas Web semântica SPARQL Séries temporais Knowledge Graph for Agricultural Prices
ISSN:	2352-3409
DOI:	https://doi.org/10.1016/j.dib.2026.112607
Type of Material:	Artigo de periódico
Access:	openAccess
Appears in Collections:	Artigo em periódico indexado (CNPTIA)