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Registro Completo |
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Biblioteca(s): |
Embrapa Agricultura Digital; Embrapa Solos. |
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Data corrente: |
08/03/2018 |
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Data da última atualização: |
09/03/2018 |
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Tipo da produção científica: |
Capítulo em Livro Técnico-Científico |
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Autoria: |
PIEROZZI JUNIOR, I.; BERTIN, P. R. B.; MACHADO, C. R. de L.; SILVA, A. R. da. |
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Afiliação: |
IVO PIEROZZI JUNIOR, CNPTIA; PATRICIA ROCHA BELLO BERTIN, SDI; CLAUDIA REGINA DE LAIA MACHADO, CNPS; ALESSANDRA RODRIGUES DA SILVA, SCT. |
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Título: |
Towards semantic knowledge maps applications: modelling the ontological nature of data and information governance in a R&D organization. |
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Ano de publicação: |
2018 |
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Fonte/Imprenta: |
In: THOMAS, C. (Ed.). Ontology in information science. Rijeka: InTech, 2018. chap. 4, p. 83-104. |
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ISBN: |
978-953-51-3888-4 |
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DOI: |
http://dx.doi.org/10.5772/67978 |
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Idioma: |
Inglês |
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Notas: |
Na publicação: Claudia De Laia Machado. |
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Conteúdo: |
In organizational management, it is highly recommended that data and information be adequately prepared to match the knowledge needed to be used in decision-making processes. However, faced with the paradigm of complexity that currently dictates the dynamics of modern organizations, there is still a search for operational solutions that allow agility and flexibility to corporate information flows to meet that desired condition. In this context, the concept of data and information governance presents itself as a fundamental premise because it systematizes, reorganizes and reorients each element of the organizational system (people, processes, structures, etc.) without losing the notion of its contexts and causalities. For this, in the conceptual modelling of governance, the concept of systemism arises to support the balance between holistic and reductionist approaches, inherent in management processes, but often considered antagonistic or contradictory. The present chapter presents and discusses a data and information governance model for research and development (R&D) organizations. The model is based upon the concepts of data, information and knowledge life cycles and knowledge mapping, recovering and valuing the ontological nature of the elements of the system under analysis and constructing a pragmatic proposal for corporate application and operation |
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Palavras-Chave: |
Data management; Gerenciamento de dados; Gestão da informação; Knowledge management; Knowledge mapping; Mapas semânticos; Mapeamento do conhecimento; Semantic maps. |
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Thesagro: |
Gestão do Conhecimento; Pesquisa agrícola. |
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Thesaurus Nal: |
Agricultural research; Information management; Knowledge. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/173689/1/PL-Towards-Pierozzi-etal.pdf
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Marc: |
LEADER 02574naa a2200349 a 4500
001 2088829
005 2018-03-09
008 2018 bl uuuu u00u1 u #d
020 $a978-953-51-3888-4
024 7 $ahttp://dx.doi.org/10.5772/67978$2DOI
100 1 $aPIEROZZI JUNIOR, I.
245 $aTowards semantic knowledge maps applications$bmodelling the ontological nature of data and information governance in a R&D organization.$h[electronic resource]
260 $c2018
500 $aNa publicação: Claudia De Laia Machado.
520 $aIn organizational management, it is highly recommended that data and information be adequately prepared to match the knowledge needed to be used in decision-making processes. However, faced with the paradigm of complexity that currently dictates the dynamics of modern organizations, there is still a search for operational solutions that allow agility and flexibility to corporate information flows to meet that desired condition. In this context, the concept of data and information governance presents itself as a fundamental premise because it systematizes, reorganizes and reorients each element of the organizational system (people, processes, structures, etc.) without losing the notion of its contexts and causalities. For this, in the conceptual modelling of governance, the concept of systemism arises to support the balance between holistic and reductionist approaches, inherent in management processes, but often considered antagonistic or contradictory. The present chapter presents and discusses a data and information governance model for research and development (R&D) organizations. The model is based upon the concepts of data, information and knowledge life cycles and knowledge mapping, recovering and valuing the ontological nature of the elements of the system under analysis and constructing a pragmatic proposal for corporate application and operation
650 $aAgricultural research
650 $aInformation management
650 $aKnowledge
650 $aGestão do Conhecimento
650 $aPesquisa agrícola
653 $aData management
653 $aGerenciamento de dados
653 $aGestão da informação
653 $aKnowledge management
653 $aKnowledge mapping
653 $aMapas semânticos
653 $aMapeamento do conhecimento
653 $aSemantic maps
700 1 $aBERTIN, P. R. B.
700 1 $aMACHADO, C. R. de L.
700 1 $aSILVA, A. R. da
773 $tIn: THOMAS, C. (Ed.). Ontology in information science. Rijeka: InTech, 2018. chap. 4, p. 83-104.
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Embrapa Agricultura Digital (CNPTIA) |
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