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| Registros recuperados : 8 | |
| 4. |  | CRUZ, S. M. S. da; NASCIMENTO, J. A. P. do. SisGExp: Rethinking long-tail agronomic experiments. In: MATOSO, M.; GLAVIC, B. (Ed.). Provenance and annotation of data and processes. Berlin: Springer, 2016. Proceedings of the 6th International Provenance and Annotation Workshop, IPAW 2016, held in McLean, VA, USA, in June 2016.| Biblioteca(s): Embrapa Agrobiologia. |
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| 5. | | DRUCKER, D. P.; CRUZ, S. M. S. da; TELLES, M. A.; FERREIRA, A. P. L.; CORRÊA, F. E.; BERTIN, P. R. B.; MARASSI, L.; AQUINO, K.; BEZERRA, G.; CRUZ, P. V.; SOARES, F. M. Desdobramentos da implementacão da Rede GO FAIR Agro Brasil no biênio 2021-2023. In: CONGRESSO BRASILEIRO DE AGROINFORMÁTICA, 14., 2023, Natal. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2023. p. 286-293. SBIAgro 2023.| Biblioteca(s): Embrapa Agricultura Digital; Embrapa Agroenergia; Embrapa Unidades Centrais. |
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| 6. | | DRUCKER, D. P.; CRUZ, S. M. S. da; SARAIVA, A. M.; FORTALEZA, J. M.; BERTIN, P. R. B.; SIMAO, V. P. M.; TELLES, M. A.; SILVA, A. R. da; SANTOS, P. S. S.; MACARIO, C. G. do N. Implantação da Rede Temática GO-FAIR Agro Brasil: primeiros passos. In: CONGRESSO BRASILEIRO DE AGROINFORMÁTICA, 13., 2021, Bagé. Anais [...]. Bagé: Unipampa, 2021. p. 164-171. 2177-9724 Organizado por Ana Paula Lüdtke Ferreira.| Biblioteca(s): Embrapa Meio Ambiente; Embrapa Unidades Centrais. |
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| 7. | | DRUCKER, D. P.; CRUZ, S. M. S. da; SARAIVA, A. M.; FORTALEZA, J. M.; BERTIN, P. R. B.; SIMAO, V. P. M.; TELLES, M. A.; SILVA, A. R. da; SANTOS, P. S. S.; MACARIO, C. G. do N. Implantação da Rede Temática GO-FAIR Agro Brasil: primeiros passos. In: CONGRESSO BRASILEIRO DE AGROINFORMÁTICA, 13., 2021, Bagé. Anais [...]. Bagé: Unipampa, 2021. p. 164-171. 2177-9724 Organizado por Ana Paula Lüdtke Ferreira. SBIAgro 2021.| Biblioteca(s): Embrapa Agricultura Digital. |
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| 8. | | SOARES, F. M.; BERGIER, I.; CORADINI, M. C.; FERREIRA, A. P. L.; TELLES, M. A.; MACULAN, B. C. M. dos S.; ALENCAR, M. de C. F.; SIMAO, V. P. M.; ALMEIDA, B. T. de; DRUCKER, D. P.; VIEIRA, M. dos S. M.; CRUZ, S. M. S. da. Unveiling knowledge organization systems' artifacts for digital agriculture with lexical network analysis. In: INTERNATIONAL WORKSHOP ON CONCEPTUAL MODELING FOR LIFE SCIENCES, 4.; WORKSHOP ON CONCEPTUAL MODELING, ONTOLOGIES AND (META)DATA MANAGEMENT FOR FINDABLE, ACCESSIBLE, INTEROPERABLE AND REUSABLE (FAIR) DATA, 3.; INTERNATIONAL WORKSHOP ON EMPIRICAL METHODS IN CONCEPTUAL MODELING, 6.; INTERNATIONAL WORKSHOP ON DIGITAL JUSTICE, DIGITAL LAW AND CONCEPTUAL MODELING, 2.; INTERNATIONAL WORKSHOP ON ONTOLOGIES AND CONCEPTUAL MODELING. 9.; INTERNATIONAL WORKSHOP ON QUALITY AND MEASUREMENT OF MODEL-DRIVEN SOFTWARE DEVELOPMENT, 4.; WORKSHOP ON CONTROLLED VOCABULARIES AND DATA PLATFORMS FOR SMART FOOD SYSTEMS, 1., 2023, Lisbon. Advances in conceptual modeling: proceedings. Cham: Springer, 2023. p. 299-311. (Lecture notes in computer science, 14319). Editors: Tiago Prince Sales, João Araújo, José Borbinha, Giancarlo Guizzardi. ER 2023 Workshops.| Biblioteca(s): Embrapa Agricultura Digital; Embrapa Territorial; Embrapa Unidades Centrais. |
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| Registros recuperados : 8 | |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Agrobiologia. Para informações adicionais entre em contato com cnpab.biblioteca@embrapa.br. |
Registro Completo
|
Biblioteca(s): |
Embrapa Agrobiologia. |
|
Data corrente: |
09/06/2017 |
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Data da última atualização: |
20/07/2017 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 1 |
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Autoria: |
CRUZ, S. M. S. da; NASCIMENTO, J. A. P. do. |
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Afiliação: |
SERGIO MANUEL SERRA DA CRUZ, UFRRJ; JOSE ANTONIO PIRES DO NASCIMENTO, CNPAB. |
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Título: |
Enriching agronomic experiments with data provenance. |
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Ano de publicação: |
2017 |
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Fonte/Imprenta: |
International Journal of Agricultural and Environmental Information Systems , v. 8, n. 3, p. 18, 2017. |
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ISSN: |
1947-3192 |
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DOI: |
10.4018/IJAEIS.2017070102 |
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Idioma: |
Inglês |
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Conteúdo: |
Reproducibility is a major feature of Science. Even agronomic research of exemplary quality may have irreproducible empirical findings because of random or systematic error. The ability to reproduce agronomic experiments based on statistical data and legacy scripts are not easily achieved. We propose RFlow, a tool that aid researchers to manage, share, and enact the scientific experiments that encapsulate legacy R scripts. RFlow transparently captures provenance of scripts and endows experiments reproducibility. Unlike existing computational approaches, RFlow is non-intrusive, does not require users to change their working way, it wraps agronomic experiments in a scientific workflow system. Our computational experiments show that the tool can collect different types of provenance metadata of real experiments and enrich agronomic data with provenance metadata. This study shows the potential of RFlow to serve as the primary integration platform for legacy R scripts, with implications for other data- and compute-intensive agronomic projects. |
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Palavras-Chave: |
Scientific workflow system. |
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Thesaurus NAL: |
reproducibility. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
|
Marc: |
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001 2070766
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008 2017 bl uuuu u00u1 u #d
022 $a1947-3192
024 7 $a10.4018/IJAEIS.2017070102$2DOI
100 1 $aCRUZ, S. M. S. da
245 $aEnriching agronomic experiments with data provenance.$h[electronic resource]
260 $c2017
520 $aReproducibility is a major feature of Science. Even agronomic research of exemplary quality may have irreproducible empirical findings because of random or systematic error. The ability to reproduce agronomic experiments based on statistical data and legacy scripts are not easily achieved. We propose RFlow, a tool that aid researchers to manage, share, and enact the scientific experiments that encapsulate legacy R scripts. RFlow transparently captures provenance of scripts and endows experiments reproducibility. Unlike existing computational approaches, RFlow is non-intrusive, does not require users to change their working way, it wraps agronomic experiments in a scientific workflow system. Our computational experiments show that the tool can collect different types of provenance metadata of real experiments and enrich agronomic data with provenance metadata. This study shows the potential of RFlow to serve as the primary integration platform for legacy R scripts, with implications for other data- and compute-intensive agronomic projects.
650 $areproducibility
653 $aScientific workflow system
700 1 $aNASCIMENTO, J. A. P. do
773 $tInternational Journal of Agricultural and Environmental Information Systems$gv. 8, n. 3, p. 18, 2017.
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Embrapa Agrobiologia (CNPAB) |
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