KGAP: an RDF knowledge graph of agricultural commodity prices.

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dc.contributorFILIPI 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.
dc.creatorSOARES, F. M.
dc.creatorPIRES, L. F.
dc.creatorCORRÊA, F. E.
dc.creatorSANTOS, L. O. B. da S.
dc.creatorBRAGHETTO, K. L.
dc.creatorMOREIRA, D. de A.
dc.creatorDRUCKER, D. P.
dc.creatorDELBEM, A. C. B.
dc.creatorSARAIVA, A. M.
dc.date2026-03-09T11:48:33Z
dc.date2026-03-09T11:48:33Z
dc.date2026-03-09
dc.date2026
dc.date.accessioned2026-07-07T04:18:35Z
dc.descriptionThis 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.
dc.identifierData in Brief, v. 65, 112607, Apr. 2026.
dc.identifier2352-3409
dc.identifierhttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1185170
dc.identifierhttps://doi.org/10.1016/j.dib.2026.112607
dc.identifier.urihttp://hdl.handle.net/123456789/457353
dc.languageeng
dc.rightsopenAccess
dc.subjectProdutos agrícolas
dc.subjectWeb semântica
dc.subjectSPARQL
dc.subjectSéries temporais
dc.subjectKnowledge Graph for Agricultural Prices
dc.subjectEconomia Agrícola
dc.subjectPreço
dc.subjectAgricultural economics
dc.subjectAgricultural products
dc.subjectPrices
dc.subjectTime series analysis
dc.titleKGAP: an RDF knowledge graph of agricultural commodity prices.
dc.typeArtigo de periódico

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