Semantic concept schema of the linear mixed model of experimental observations

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المؤلفون: Paweł Krajewski; Augustyn Markiewicz; Emilie J. Millet; Susanna-Assunta Sansone; Agnieszka Ławrynowicz; Fred A. van Eeuwijk; Alejandra Gonzalez-Beltran; Hanna Ćwiek-Kupczyńska; Philippe Rocca-Serra; Katarzyna Filipiak
المصدر:
Scientific Data, Vol 7, Iss 1, Pp 1-13 (2020)
Scientific Data
Scientific Data, 2020, 7 (1), pp.70. ⟨10.1038/s41597-020-0409-7⟩
Scientific Data, 7(1)
Scientific Data 7 (2020) 1
الموضوع:
Mixed model; Statistics and Probability; Statistical methods; Classification and taxonomy; Computer science; Data management; 0206 medical engineering; 02 engineering and technology; Ontology (information science); Library and Information Sciences; Semantic data model; Wiskundige en Statistische Methoden - Biometris; Article; Generalized linear mixed model; Education; 03 medical and health sciences; Schema (psychology); Life Science; Computational models; lcsh:Science; Mathematical and Statistical Methods - Biometris; 030304 developmental biology; 0303 health sciences; Information Age; Information retrieval; business.industry; Statistical model; PE&RC; Computer Science Applications; Data processing; [STAT]Statistics [stat]; Data integration; lcsh:Q; Statistics, Probability and Uncertainty; business; 020602 bioinformatics; Information Systems
اللغة:
English
الدخول الالكتروني :
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9ec2ea9008639959d19b1bba6f1369e0
http://link.springer.com/article/10.1038/s41597-020-0409-7

معلومة اضافية
- Contributors:
  Institute of Plant Genetics (IPG); Polish Academy of Sciences (PAN); Poznan University of Technology (PUT); Department of Mathematical and Statistical Methods; Poznan University of Life Sciences; Oxford e-Research Center; University of Oxford; Génétique et Amélioration des Fruits et Légumes (GAFL); Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE); Biometris; Wageningen University and Research [Wageningen] (WUR); Narodowe Centrum Nauki (National Science Centre) 2016/21/N/ST6/02358UK Research & Innovation (UKRI) Biotechnology and Biological Sciences Research Council (BBSRC)BB/L024101/1BB/L005069/1United States Department of Health & Human Services National Institutes of Health (NIH) - USAU54 AI1179251U24AI117966-011OT3OD025459-01 1OT3OD025467-011OT3OD025462-01IMI116060UK Research & Innovation (UKRI) Biotechnology and Biological Sciences Research Council (BBSRC)BB/I000771/1BB/L005069/1BB/E025080/1BB/L024101/1BB/H024921/1; European Project: 634107,H2020,H2020-PHC-2014-two-stage,MULTIMOT(2015); European Project: 654241,H2020,H2020-EINFRA-2014-2,PhenoMeNal(2015); European Project: 676559,H2020,H2020-INFRADEV-1-2015-1,ELIXIR-EXCELERATE(2015)
- بيانات النشر:
  Nature Publishing Group, 2020.
- الموضوع:
  2020
- نبذة مختصرة :
  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.
- File Description:
  application/pdf
- ISSN:
  2052-4463
- Rights:
  OPEN
- الرقم المعرف:
  edsair.doi.dedup.....9ec2ea9008639959d19b1bba6f1369e0

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