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Semantic concept schema of the linear mixed model of experimental observations.
Cwiek-Kupczynska, Hanna; Filipiak, Katarzyna; Markiewicz, Augustyn; Rocca-Serra, Philippe; Gonzalez-Beltran, Alejandra N; Sansone, Susanna-Assunta; Millet, Emilie J; van Eeuwijk, Fred; Lawrynowicz, Agnieszka; Krajewski, Pawel.
Afiliación
  • Cwiek-Kupczynska H; Institute of Plant Genetics, Polish Academy of Sciences, ul. Strzeszynska 34, 60-479, Poznan, Poland.
  • Filipiak K; Institute of Mathematics, Poznan University of Technology, ul. Piotrowo 3a, 60-965, Poznan, Poland.
  • Markiewicz A; Department of Mathematical and Statistical Methods, Poznan University of Life Sciences, ul. Wojska Polskiego 28, 60-637, Poznan, Poland.
  • Rocca-Serra P; Oxford e-Research Center, Department of Engineering Science, University of Oxford, Oxford, OX1 3QG, UK.
  • Gonzalez-Beltran AN; Oxford e-Research Center, Department of Engineering Science, University of Oxford, Oxford, OX1 3QG, UK.
  • Sansone SA; Scientific Computing Department, Science and Technology Facilities Council, UK Research & Innovation, Didcot, OX11 0QX, UK.
  • Millet EJ; Oxford e-Research Center, Department of Engineering Science, University of Oxford, Oxford, OX1 3QG, UK.
  • van Eeuwijk F; Biometris, Wageningen University & Research Centre, P.O. Box 16, 6700 AA, Wageningen, The Netherlands.
  • Lawrynowicz A; Biometris, Wageningen University & Research Centre, P.O. Box 16, 6700 AA, Wageningen, The Netherlands.
  • Krajewski P; Faculty of Computing and Telecommunications, Poznan University of Technology, ul. Piotrowo 3, 60-965, Poznan, Poland.
Sci Data ; 7(1): 70, 2020 02 27.
Article en En | MEDLINE | ID: mdl-32109232
In the information age, smart data modelling and data management can be carried out to address the wealth of data produced in scientific experiments. In this paper, we propose a semantic model for the statistical analysis of datasets by linear mixed models. We tie together disparate statistical concepts in an interdisciplinary context through the application of ontologies, in particular the Statistics Ontology (STATO), to produce FAIR data summaries. We hope to improve the general understanding of statistical modelling and thus contribute to a better description of the statistical conclusions from data analysis, allowing their efficient exploration and automated processing.

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Sci Data Año: 2020 Tipo del documento: Article País de afiliación: Polonia Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Sci Data Año: 2020 Tipo del documento: Article País de afiliación: Polonia Pais de publicación: Reino Unido