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| Registros recuperados : 5 | |
| 1. |  | PEIXOTO, M. A.; EVANGELISTA, J. S. P. C.; COELHO, I. F.; CARVALHO, L. P. de; FARIAS, F. J. C.; TEODORO, P. E.; BHERING, L. L. Genotype selection based on multiple traits in cotton crops: the application of genotype by yield trait biplot. Acta Scientiarum. Agronomy, v. 44, e54136, 2022.| Biblioteca(s): Embrapa Algodão. |
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| 2. | | EVANGELISTA, J. S. P. C.; PEIXOTO, M. A.; COELHO, I. F.; ALVES, R. S.; SILVA, F. F. e; RESENDE, M. D. V. de; SILVA, F. L. da; BHERING, L. L. Environmental stratification and genotype recommendation toward the soybean ideotype: a Bayesian approach. Crop Breeding and Applied Biotechnology, v. 21, n. 1, e359721111, 2021.| Biblioteca(s): Embrapa Café. |
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| 3. | | PEIXOTO, M. A.; EVANGELISTA, J. S. P. C.; COELHO, I. F; ALVES, R. A.; LAVIOLA, B. G.; SILVA, F. F. e; RESENDE, M. D. V. de; BHERING, L. L. Multiple-trait model through Bayesian inference applied to Jatropha curcas breeding for bioenergy. PLOS ONE , v. 16, n. 3, e0247775, Mar. 2021. 16| Biblioteca(s): Embrapa Agroenergia; Embrapa Café. |
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| 4. | | FERREIRA, F. M.; CHAVES, S. F. da S.; PEIXOTO, M. A.; ALVES, R. S.; COELHO, I. F.; RESENDE, M. D. V. de; SANTOS, G. A. dos; BHERING, L. L. Multi-trait multi-environment models for selecting high-performance and stable eucalyptus clones. Acta Scientiarum. Agronomy, v. 45, e61626, 2023. 9 p.| Biblioteca(s): Embrapa Café. |
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| 5. | | EVANGELISTA, J. S. P. C.; PEIXOTO, M. A.; COELHO, I. F.; FERREIRA, F. M.; MARÇAL, T. de S.; ALVES, R. S.; CHAVES, S. F. da S.; RODRIGUES, E. V.; LAVIOLA, B. G.; RESENDE, M. D. V. de; DIAS, K. O. das G.; BHERING, L. L. Modeling covariance structures and optimizing jatropha curcas breeding. Tree Genetics & Genomes, v. 19, 21, 2023. 11 p.| Biblioteca(s): Embrapa Agroenergia; Embrapa Café. |
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| Registros recuperados : 5 | |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Agricultura Digital. Para informações adicionais entre em contato com cnptia.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
17/12/2009 |
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Data da última atualização: |
15/01/2020 |
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Tipo da produção científica: |
Artigo em Anais de Congresso / Nota Técnica |
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Autoria: |
MACÁRIO, C. G. N.; SOUSA, S. R. de; MEDEIROS, C. B. |
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Afiliação: |
CARLA GEOVANA DO NASCIMENTO MACARIO, CNPTIA; SIDNEY ROBERTO DE SOUSA, Unicamp; CLAUDIA BAUZER MEDEIROS, Unicamp. |
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Título: |
Annotating geospatial data based on its semantics. |
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Ano de publicação: |
2009 |
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Fonte/Imprenta: |
In: ACM SIGSPATIAL INTERNATIONAL CONFERENCE ON ADVANCES IN GEOGRAPHIC INFORMATION SYSTEMS, 17., 2009, Seattle. Proceedings... NewYork: ACM, 2009. |
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Páginas: |
p. 81-90. |
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Idioma: |
Inglês |
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Notas: |
ACM SIGSPATIAL GIS 2009. |
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Conteúdo: |
Geospatial information (GI) constitutes a significant portion of available data and are a key factor in planning and decision-making in a variety of domains, such as emergency management and agriculture. However, to be used, these data have to be interpreted, sometimes producing new data and information. This new information is generally embedded on additional files, or remains on experts' brains. Hence, every time a user wants to use its knowledge, data have to be interpreted again. This paper presents a framework for alleviating this problem based on semi-automatic annotation of geospatial data. This framework is described in detail, as well the choices made in its design and implementation. At the end, we present a case study in agriculture, used to validate our proposal. |
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Palavras-Chave: |
Anotação semântica; Dados geoespaciais; Geospatial standards; Semantic annotation; Semantic interoperability. |
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Thesaurus NAL: |
Spatial data. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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Marc: |
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001 1578320
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100 1 $aMACÁRIO, C. G. N.
245 $aAnnotating geospatial data based on its semantics.$h[electronic resource]
260 $aIn: ACM SIGSPATIAL INTERNATIONAL CONFERENCE ON ADVANCES IN GEOGRAPHIC INFORMATION SYSTEMS, 17., 2009, Seattle. Proceedings... NewYork: ACM$c2009
300 $ap. 81-90.
500 $aACM SIGSPATIAL GIS 2009.
520 $aGeospatial information (GI) constitutes a significant portion of available data and are a key factor in planning and decision-making in a variety of domains, such as emergency management and agriculture. However, to be used, these data have to be interpreted, sometimes producing new data and information. This new information is generally embedded on additional files, or remains on experts' brains. Hence, every time a user wants to use its knowledge, data have to be interpreted again. This paper presents a framework for alleviating this problem based on semi-automatic annotation of geospatial data. This framework is described in detail, as well the choices made in its design and implementation. At the end, we present a case study in agriculture, used to validate our proposal.
650 $aSpatial data
653 $aAnotação semântica
653 $aDados geoespaciais
653 $aGeospatial standards
653 $aSemantic annotation
653 $aSemantic interoperability
700 1 $aSOUSA, S. R. de
700 1 $aMEDEIROS, C. B.
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Registro original: |
Embrapa Agricultura Digital (CNPTIA) |
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