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Registro Completo |
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Biblioteca(s): |
Embrapa Instrumentação. |
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Data corrente: |
25/10/2021 |
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Data da última atualização: |
09/06/2022 |
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Tipo da produção científica: |
Artigo em Anais de Congresso |
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Autoria: |
NEVES, R. A.; CRUVINEL, P. E. |
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Afiliação: |
PAULO ESTEVAO CRUVINEL, CNPDIA. |
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Título: |
Ontology for structuring a digital databases for decision making in grain production. |
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Ano de publicação: |
2021 |
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Fonte/Imprenta: |
In: IEEE International Conference on Semantic Computing (ICSC), 15th, Laguna Hills, CA, USA, 2021. |
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Páginas: |
386-392 |
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DOI: |
10.1109/ICSC50631.2021.00071 |
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Idioma: |
Inglês |
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Conteúdo: |
This paper presents an ontology for the structuring of digital databases with the objective of acting in a cloud environment and meeting big data sources in the agricultural context of grain production. Its conception is structured in three stages: the first stage presents an ontological architecture aimed at public and private cloud environments, the second stage deals with a semantic model at process level, and a pseudocode for ontological application is elaborated in the third stage, considering the technologies applied to the cloud. This work combines advanced features to support decision making from Data Lake storage solutions, semantic treatment of big data, as well as the presentation of strategies based on machine learning and data quality analysis to obtain data and metadata organized for application in a decision model. The configuration of the ontology presented meets the diversity of big data projects in the grain production context, the characteristics of which are based on interoperability in the use of heterogeneous data and its integration, elasticity of computational resources, and high availability of cloud access. |
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Palavras-Chave: |
Big Data; Cloud Computing; Terms-Ontology. |
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Categoria do assunto: |
-- |
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Marc: |
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001 2135527
005 2022-06-09
008 2021 bl uuuu u00u1 u #d
024 7 $a10.1109/ICSC50631.2021.00071$2DOI
100 1 $aNEVES, R. A.
245 $aOntology for structuring a digital databases for decision making in grain production.$h[electronic resource]
260 $aIn: IEEE International Conference on Semantic Computing (ICSC), 15th, Laguna Hills, CA, USA$c2021
300 $a386-392
520 $aThis paper presents an ontology for the structuring of digital databases with the objective of acting in a cloud environment and meeting big data sources in the agricultural context of grain production. Its conception is structured in three stages: the first stage presents an ontological architecture aimed at public and private cloud environments, the second stage deals with a semantic model at process level, and a pseudocode for ontological application is elaborated in the third stage, considering the technologies applied to the cloud. This work combines advanced features to support decision making from Data Lake storage solutions, semantic treatment of big data, as well as the presentation of strategies based on machine learning and data quality analysis to obtain data and metadata organized for application in a decision model. The configuration of the ontology presented meets the diversity of big data projects in the grain production context, the characteristics of which are based on interoperability in the use of heterogeneous data and its integration, elasticity of computational resources, and high availability of cloud access.
653 $aBig Data
653 $aCloud Computing
653 $aTerms-Ontology
700 1 $aCRUVINEL, P. E.
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