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Application of Hierarchical Visualization Techniques in Meta-Analysis Data
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Author(s): Bruna Rossetto Delazeri (Department of Informatics, State University of Ponta Grossa, Ponta Grossa, Brazil), Felipe Paes Gusmão (Federal Technological University of Parana, Ponta Grossa, Brazil), Simone Nasser Matos (Department of Computer Science, Federal Technological University of Parana, Ponta Grossa, Brazil), Alaine Margarete Guimarães (Department of Computer Science, State University of Ponta Grossa, Ponta Grossa, Brazil)and Marcelo Giovanetti Canteri (Department of Agronomy, Londrina State University, Londrina, Brazil)
Copyright: 2018
Volume: 9
Issue: 1
Pages: 15
Source title:
International Journal of Agricultural and Environmental Information Systems (IJAEIS)
Editor(s)-in-Chief: Frederic Andres (National Institute of Informatics, Japan), Chutiporn Anutariya (Asian Institute of Technology, Thailand), Teeradaj Racharak (Japan Advanced Institute of Science and Technology, Japan)and Watanee Jearanaiwongkul (National institute of Informatics, Japan)
DOI: 10.4018/IJAEIS.2018010101
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Abstract
The meta-analysis is a probabilistic technique that groups the results of several studies, approaches the same subject and produces a result that summarizes the whole. The results that are displayed in graphical form neither offer interactivity with the user, nor a user-friendly interface and easy comprehension. In order to obtain a visual exploratory analysis with more satisfactory results, there are information visualization techniques applied to map the data in graphical form to broaden the user cognition. This article performs the execution of the meta-analysis, through R software, in order to determine the efficiency of fungicide fluquinconazole when combating Asian soy rust and applies the Technique for the Visualization of Hierarchical Information Structure; the Bifocal Tree, to improve the results displayed by the R through the forest plot graphic.
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