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Displaying Bivariate Data with Developed Cloud Based Data Visualization Tool

Year 2024, Volume: 12 Issue: 2, 150 - 157, 28.10.2024

Abstract

Data visualization is one of the hot topics of statistics. Programming languages such as R and Python are needed to create high-quality graphs. However, these programs are quite complex to use and difficult for researchers with no programming background. In this study, a cloud-based web application, named DATAVIS2, is developed to draw bivariate graphs. The developed application works independently of the operating system and the web browser. The DATAVIS2 web-tool includes fourteen different graphs for quantitative and categorical variables. The developed web-tool is available at https://beststat.shinyapps.io/datavis2/.

References

  • [1] Chang, W. (2021). shinythemes: Themes for Shiny. R package version 1.2.0. https://CRAN.R-project.org/package=shinythemes
  • [2] Chang, W. and Ribeiro, B.B. (2018). shinydashboard: Create Dashboards with ’Shiny’. R package version 0.7.1. https://CRAN.Rproject. org/package=shinydashboard
  • [3] Anouncia, S. M., Gohel, H. A. and Vairamuthu, S. (Eds.). (2020). Data Visualization: Trends and Challenges Toward Multidisciplinary Perception. Springer Nature.
  • [4] Barker, T. and Canning, M. (2013). Pro Data Visualization using R and JavaScript (No. s 207). New York, NY: Apress.
  • [5] Chang, W., Cheng, J., Allaire, J.J., Sievert, C. Schloerke, B., Xie, Y., Allen, J., McPherson, J., Dipert, A. and Borges, B. (2021). shiny: Web Application Framework for R. R package version 1.6.0. https://CRAN.R-project.org/package=shiny
  • [6] Chen, D., Fu, L. Y., Hu, D., Klukas, C., Chen, M. and Kaufmann, K. (2018). The HTPmod Shiny application enables modeling and visualization of large-scale biological data. Communications Biology, 1(1), 1-8.
  • [7] Do, A. L., Boccaletti, S., Epperlein, J., Siegmund, S. and Gross, T. (2016). Topological stability criteria for networking dynamical systems with Hermitian Jacobian. European Journal of Applied Mathematics, 27(6), 888-903.
  • [8] Clarke, E. and Sherrill-Mix, S. (2017). ggbeeswarm: Categorical Scatter (Violin Point) Plots. R package version 0.6.0. https://CRAN.Rproject. org/package=ggbeeswarm
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  • [10] G¨ursoy, A. (2022). Construction of networks by associating with submanifolds of almost Hermitian manifolds. Fundamental Journal of Mathematics and Applications, 5(1), 21-31.
  • [11] Hoser, B. and Geyer-Schulz, A. (2005). Eigenspectral analysis of hermitian adjacency matrices for the analysis of group substructures. Journal of Mathematical Sociology, 29(4), 265-294.
  • [12] Kayaturan, G. C. (2022). Error Elimination From Bloom Filters in Computer Networks Represented by Graphs. Fundamental Journal of Mathematics and Applications, 5(4), 240-244.
  • [13] Mullan, K. A., Bramberger, L. M., Munday, P. R., Goncalves, G., Revote, J., Mifsud, N. A., ... and Li, C. (2021). ggVolcanoR: A Shiny app for customizable visualization of differential expression datasets. Computational and Structural Biotechnology Journal, 19, 5735-5740.
  • [14] Post, F. H., Nielson, G. and Bonneau, G. P. (Eds.). (2002). Data visualization: The state of the art.
  • [15] Postma, M. and Goedhart, J. (2019). PlotsOfData-A web app for visualizing data together with their summaries. PLoS Biology, 17(3), e3000202.
  • [16] Reyes, A. L. P., Silva, T. C., Coetzee, S. G., Plummer, J. T., Davis, B. D., Chen, S., ... and Jones, M. R. (2019). GENAVi: a shiny web application for gene expression normalization, analysis and visualization. BMC genomics, 20(1), 1-9.
  • [17] Tebe, C., Valls, J., Satorra, P. and Tobias, A. (2020). COVID19-world: a shiny application to perform comprehensive country-specific data visualization for SARS-CoV-2 epidemic. BMC Medical Research Methodology, 20(1), 1-7.
  • [18] Verity, R., Collins, C., Card, D. C., Schaal, S. M., Wang, L. and Lotterhos, K. E. (2017). minotaur: A platform for the analysis and visualization of multivariate results from genome scans with R Shiny. Molecular ecology resources, 17(1), 33-43.
  • [19] Wickham, H. and Seidel, D. (2020). scales: Scale Functions for Visualization. R package version 1.1.1. https://CRAN.R-project.org/package=scales
  • [20] Wickham, H. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York, 2016
  • [21] Wickham, H., Francois, R., Henry, L. and Muller, K. (2021). dplyr: A Grammar of Data Manipulation. R package version 1.0.7. https://CRAN.Rproject. org/package=dplyr
  • [22] Wilke, C.O. (2021). ggridges: Ridgeline Plots in ’ggplot2’. R package version 0.5.3. https://CRAN.R-project.org/package=ggridges
  • [23] Wilkins, D. (2021). treemapify: Draw Treemaps in ’ggplot2’. R package version 2.5.5. https://CRAN.R-project.org/package=treemapify
  • [24] Yu, Y., Ouyang, Y. and Yao, W. (2018). shinyCircos: an R/Shiny application for interactive creation of Circos plot. Bioinformatics, 34(7), 1229-1231.
Year 2024, Volume: 12 Issue: 2, 150 - 157, 28.10.2024

Abstract

References

  • [1] Chang, W. (2021). shinythemes: Themes for Shiny. R package version 1.2.0. https://CRAN.R-project.org/package=shinythemes
  • [2] Chang, W. and Ribeiro, B.B. (2018). shinydashboard: Create Dashboards with ’Shiny’. R package version 0.7.1. https://CRAN.Rproject. org/package=shinydashboard
  • [3] Anouncia, S. M., Gohel, H. A. and Vairamuthu, S. (Eds.). (2020). Data Visualization: Trends and Challenges Toward Multidisciplinary Perception. Springer Nature.
  • [4] Barker, T. and Canning, M. (2013). Pro Data Visualization using R and JavaScript (No. s 207). New York, NY: Apress.
  • [5] Chang, W., Cheng, J., Allaire, J.J., Sievert, C. Schloerke, B., Xie, Y., Allen, J., McPherson, J., Dipert, A. and Borges, B. (2021). shiny: Web Application Framework for R. R package version 1.6.0. https://CRAN.R-project.org/package=shiny
  • [6] Chen, D., Fu, L. Y., Hu, D., Klukas, C., Chen, M. and Kaufmann, K. (2018). The HTPmod Shiny application enables modeling and visualization of large-scale biological data. Communications Biology, 1(1), 1-8.
  • [7] Do, A. L., Boccaletti, S., Epperlein, J., Siegmund, S. and Gross, T. (2016). Topological stability criteria for networking dynamical systems with Hermitian Jacobian. European Journal of Applied Mathematics, 27(6), 888-903.
  • [8] Clarke, E. and Sherrill-Mix, S. (2017). ggbeeswarm: Categorical Scatter (Violin Point) Plots. R package version 0.6.0. https://CRAN.Rproject. org/package=ggbeeswarm
  • [9] Dowle, M. and Srinivasan, A. (2021). data.table: Extension of ’data.frame’. R package version 1.14.0. https://CRAN.R-project.org/package=data.table
  • [10] G¨ursoy, A. (2022). Construction of networks by associating with submanifolds of almost Hermitian manifolds. Fundamental Journal of Mathematics and Applications, 5(1), 21-31.
  • [11] Hoser, B. and Geyer-Schulz, A. (2005). Eigenspectral analysis of hermitian adjacency matrices for the analysis of group substructures. Journal of Mathematical Sociology, 29(4), 265-294.
  • [12] Kayaturan, G. C. (2022). Error Elimination From Bloom Filters in Computer Networks Represented by Graphs. Fundamental Journal of Mathematics and Applications, 5(4), 240-244.
  • [13] Mullan, K. A., Bramberger, L. M., Munday, P. R., Goncalves, G., Revote, J., Mifsud, N. A., ... and Li, C. (2021). ggVolcanoR: A Shiny app for customizable visualization of differential expression datasets. Computational and Structural Biotechnology Journal, 19, 5735-5740.
  • [14] Post, F. H., Nielson, G. and Bonneau, G. P. (Eds.). (2002). Data visualization: The state of the art.
  • [15] Postma, M. and Goedhart, J. (2019). PlotsOfData-A web app for visualizing data together with their summaries. PLoS Biology, 17(3), e3000202.
  • [16] Reyes, A. L. P., Silva, T. C., Coetzee, S. G., Plummer, J. T., Davis, B. D., Chen, S., ... and Jones, M. R. (2019). GENAVi: a shiny web application for gene expression normalization, analysis and visualization. BMC genomics, 20(1), 1-9.
  • [17] Tebe, C., Valls, J., Satorra, P. and Tobias, A. (2020). COVID19-world: a shiny application to perform comprehensive country-specific data visualization for SARS-CoV-2 epidemic. BMC Medical Research Methodology, 20(1), 1-7.
  • [18] Verity, R., Collins, C., Card, D. C., Schaal, S. M., Wang, L. and Lotterhos, K. E. (2017). minotaur: A platform for the analysis and visualization of multivariate results from genome scans with R Shiny. Molecular ecology resources, 17(1), 33-43.
  • [19] Wickham, H. and Seidel, D. (2020). scales: Scale Functions for Visualization. R package version 1.1.1. https://CRAN.R-project.org/package=scales
  • [20] Wickham, H. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York, 2016
  • [21] Wickham, H., Francois, R., Henry, L. and Muller, K. (2021). dplyr: A Grammar of Data Manipulation. R package version 1.0.7. https://CRAN.Rproject. org/package=dplyr
  • [22] Wilke, C.O. (2021). ggridges: Ridgeline Plots in ’ggplot2’. R package version 0.5.3. https://CRAN.R-project.org/package=ggridges
  • [23] Wilkins, D. (2021). treemapify: Draw Treemaps in ’ggplot2’. R package version 2.5.5. https://CRAN.R-project.org/package=treemapify
  • [24] Yu, Y., Ouyang, Y. and Yao, W. (2018). shinyCircos: an R/Shiny application for interactive creation of Circos plot. Bioinformatics, 34(7), 1229-1231.
There are 24 citations in total.

Details

Primary Language English
Subjects Applied Mathematics (Other)
Journal Section Articles
Authors

Gokcen Altun

Emrah Altun

Sümeyye İslamoğlu

Publication Date October 28, 2024
Submission Date December 5, 2023
Acceptance Date January 21, 2024
Published in Issue Year 2024 Volume: 12 Issue: 2

Cite

APA Altun, G., Altun, E., & İslamoğlu, S. (2024). Displaying Bivariate Data with Developed Cloud Based Data Visualization Tool. Konuralp Journal of Mathematics, 12(2), 150-157.
AMA Altun G, Altun E, İslamoğlu S. Displaying Bivariate Data with Developed Cloud Based Data Visualization Tool. Konuralp J. Math. October 2024;12(2):150-157.
Chicago Altun, Gokcen, Emrah Altun, and Sümeyye İslamoğlu. “Displaying Bivariate Data With Developed Cloud Based Data Visualization Tool”. Konuralp Journal of Mathematics 12, no. 2 (October 2024): 150-57.
EndNote Altun G, Altun E, İslamoğlu S (October 1, 2024) Displaying Bivariate Data with Developed Cloud Based Data Visualization Tool. Konuralp Journal of Mathematics 12 2 150–157.
IEEE G. Altun, E. Altun, and S. İslamoğlu, “Displaying Bivariate Data with Developed Cloud Based Data Visualization Tool”, Konuralp J. Math., vol. 12, no. 2, pp. 150–157, 2024.
ISNAD Altun, Gokcen et al. “Displaying Bivariate Data With Developed Cloud Based Data Visualization Tool”. Konuralp Journal of Mathematics 12/2 (October 2024), 150-157.
JAMA Altun G, Altun E, İslamoğlu S. Displaying Bivariate Data with Developed Cloud Based Data Visualization Tool. Konuralp J. Math. 2024;12:150–157.
MLA Altun, Gokcen et al. “Displaying Bivariate Data With Developed Cloud Based Data Visualization Tool”. Konuralp Journal of Mathematics, vol. 12, no. 2, 2024, pp. 150-7.
Vancouver Altun G, Altun E, İslamoğlu S. Displaying Bivariate Data with Developed Cloud Based Data Visualization Tool. Konuralp J. Math. 2024;12(2):150-7.
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