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| Registros recuperados : 192 | |
| 105. |  | OBA, E.; SOUZA, M. I. L.; URIBE-VELÁSQUEZ, L. F.; RAMOS, A. de A. Concentrações plasmáticas e ritmo circadiano de cortisol e prolactina (PRL) em ovelhas, durante o anestro estacional. Arquivos de Ciências Veterinárias e Zoologia da UNIPAR, Umuarama, v. 4, n. 2, p. 169-174, 2001.| Biblioteca(s): Embrapa Caprinos e Ovinos. |
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| 107. | | MORAES, M. A. S. de; MENDES, C. I. C.; VENDRUSCULO, L. G.; SOUZA, M. I. F. Demanda de software pela agricultura familiar: entraves e potenciais para micro e pequenas empresas desenvolvedoras de software. In: CONGRESSO BRASILEIRO DE AGROINFORMÁTICA, 7., 2009, Viçosa, MG. Anais... Viçosa, MG: UFV, 2009. Não paginado SBIAgro 2009.| Biblioteca(s): Embrapa Agricultura Digital. |
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| 120. | | SOUZA, M. I. L.; VELASQUEZ, L. F. U.; OBA, E.; RAMOS, A. de A. Ritmo circadiano de secrecao de estradiol, progesterona e FSH em ovelhas durante o anestro estacional. In: REUNIAO ANUAL DA SOCIEDADE BRASILEIRA DE ZOOTECNIA, 34., 1997, Juiz de Fora, MG. Anais... Juiz de Fora: Sociedade Brasileira de Zootecnia, 1997. p.361-363.| Biblioteca(s): Embrapa Caprinos e Ovinos. |
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| Registros recuperados : 192 | |
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Registro Completo
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
31/07/2020 |
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Data da última atualização: |
06/08/2020 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
C - 0 |
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Autoria: |
SOUZA, M. I. F.; TORRES, T. Z.; PEDROSO JUNIOR, M.; CARVALHO, J. R. P. de; TERNES, S.; SOUZA, K. X. S. de; SOUZA, G. da S. e. |
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Afiliação: |
MARCIA IZABEL FUGISAWA SOUZA, CNPTIA; TERCIA ZAVAGLIA TORRES, CNPTIA; MOACIR PEDROSO JUNIOR, SIRE; JOSE RUY PORTO DE CARVALHO, CNPTIA; SONIA TERNES, CNPTIA; KLEBER XAVIER SAMPAIO DE SOUZA, CNPTIA; GERALDO DA SILVA E SOUZA, UnB. |
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Título: |
Organizational guidelines for Embrapa advanced quantitative methods and scientific computing área. |
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Ano de publicação: |
2020 |
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Fonte/Imprenta: |
Open Journal of Business and Management, v. 8, n. 4, p. 1816-1830, July 2020. |
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DOI: |
https://doi.org/10.4236/ojbm.2020.84111 |
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Idioma: |
Inglês |
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Conteúdo: |
Abstract. This study aimed to define organizational guidelines on advanced quantitative methods and scientific computing (QMSC) for the Brazilian Agricultural Research Corporation (Embrapa), a public institution under the Brazilian Ministry of Agriculture, Livestock and Food Supply (MAPA). The study was based on a strategic and systemic perspective to support the strengthening of governance of the area of research, development and innovation (RD&I) at Embrapa. This exploratory qualitative study was conducted in two phases. In the first phase, a benchmarking study of organizational model restructuring, especially in areas of QMSC, was carried out in Brazilian and international RD&I institutions. The second phase included an analytical and critical study on the general panorama of QMSC research. Both phases supported the generation of the final result of this study, which was the formulation of a proposal for organizational guidelines for the QMSC area at Embrapa. The study presented the following main results: 1) there is no similarity between the institutions surveyed in the benchmarking and Embrapa, either in terms of the scope of institutional performance, or in relation to the interests focused on organizational innovation in the QMSC area; 2) quantitative methods and scientific computing as areas of expertise and knowledge are widely spread in Brazil, especially at Embrapa, however we did not find equivalence and/or similarity with organizational structure of international institutions. The study highlights the need to expand the scope of the QMSC area at Embrapa, due to the emergence of new fields of activity and new lines of research, for example Data Science. The study recommends Embrapa to prioritize Data Science as a strategic line of research to achieve its results, through research data use and reuse engineering, in order to generate new information and knowledge for decision-making and/or public policy formulation and management. MenosAbstract. This study aimed to define organizational guidelines on advanced quantitative methods and scientific computing (QMSC) for the Brazilian Agricultural Research Corporation (Embrapa), a public institution under the Brazilian Ministry of Agriculture, Livestock and Food Supply (MAPA). The study was based on a strategic and systemic perspective to support the strengthening of governance of the area of research, development and innovation (RD&I) at Embrapa. This exploratory qualitative study was conducted in two phases. In the first phase, a benchmarking study of organizational model restructuring, especially in areas of QMSC, was carried out in Brazilian and international RD&I institutions. The second phase included an analytical and critical study on the general panorama of QMSC research. Both phases supported the generation of the final result of this study, which was the formulation of a proposal for organizational guidelines for the QMSC area at Embrapa. The study presented the following main results: 1) there is no similarity between the institutions surveyed in the benchmarking and Embrapa, either in terms of the scope of institutional performance, or in relation to the interests focused on organizational innovation in the QMSC area; 2) quantitative methods and scientific computing as areas of expertise and knowledge are widely spread in Brazil, especially at Embrapa, however we did not find equivalence and/or similarity with organizational structure of internation... Mostrar Tudo |
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Palavras-Chave: |
Ciência de dados; Computação científica; Data Science; Diretrizes organizacionais; Gestão de pesquisa e desenvolvimento; Métodos quantitativos; Organizational Guidelines; Organizational Innovation; Quantitative Methods; RD&I Management; Research and Development Institutions; Scientific Computing. |
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Thesagro: |
Inovação. |
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Thesaurus NAL: |
Research and development; Research institutions. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/215069/1/AP-Organizational-Guidelines-2020.pdf
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Marc: |
LEADER 03250naa a2200385 a 4500
001 2124142
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008 2020 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.4236/ojbm.2020.84111$2DOI
100 1 $aSOUZA, M. I. F.
245 $aOrganizational guidelines for Embrapa advanced quantitative methods and scientific computing área.$h[electronic resource]
260 $c2020
520 $aAbstract. This study aimed to define organizational guidelines on advanced quantitative methods and scientific computing (QMSC) for the Brazilian Agricultural Research Corporation (Embrapa), a public institution under the Brazilian Ministry of Agriculture, Livestock and Food Supply (MAPA). The study was based on a strategic and systemic perspective to support the strengthening of governance of the area of research, development and innovation (RD&I) at Embrapa. This exploratory qualitative study was conducted in two phases. In the first phase, a benchmarking study of organizational model restructuring, especially in areas of QMSC, was carried out in Brazilian and international RD&I institutions. The second phase included an analytical and critical study on the general panorama of QMSC research. Both phases supported the generation of the final result of this study, which was the formulation of a proposal for organizational guidelines for the QMSC area at Embrapa. The study presented the following main results: 1) there is no similarity between the institutions surveyed in the benchmarking and Embrapa, either in terms of the scope of institutional performance, or in relation to the interests focused on organizational innovation in the QMSC area; 2) quantitative methods and scientific computing as areas of expertise and knowledge are widely spread in Brazil, especially at Embrapa, however we did not find equivalence and/or similarity with organizational structure of international institutions. The study highlights the need to expand the scope of the QMSC area at Embrapa, due to the emergence of new fields of activity and new lines of research, for example Data Science. The study recommends Embrapa to prioritize Data Science as a strategic line of research to achieve its results, through research data use and reuse engineering, in order to generate new information and knowledge for decision-making and/or public policy formulation and management.
650 $aResearch and development
650 $aResearch institutions
650 $aInovação
653 $aCiência de dados
653 $aComputação científica
653 $aData Science
653 $aDiretrizes organizacionais
653 $aGestão de pesquisa e desenvolvimento
653 $aMétodos quantitativos
653 $aOrganizational Guidelines
653 $aOrganizational Innovation
653 $aQuantitative Methods
653 $aRD&I Management
653 $aResearch and Development Institutions
653 $aScientific Computing
700 1 $aTORRES, T. Z.
700 1 $aPEDROSO JUNIOR, M.
700 1 $aCARVALHO, J. R. P. de
700 1 $aTERNES, S.
700 1 $aSOUZA, K. X. S. de
700 1 $aSOUZA, G. da S. e
773 $tOpen Journal of Business and Management$gv. 8, n. 4, p. 1816-1830, July 2020.
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Embrapa Agricultura Digital (CNPTIA) |
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