shiny::runGitHub('jbryer/ShinyPoster') see an example poster.
Go to https://github.com/jbryer/ShinyPoster to download the template
In the past several years academic conferences have begun to display poster presentations electronically. This provides an opportunity for authors to include interactivity into their posters. Shiny has become a popular and powerful framework for researchers to create interactive web applications. This poster and paper presents a framework for creating traditional two or three column posters using Shiny. This provides the opportunity for the inclusion of interactive and live components in the poster.
A template for the Shiny Poster is available on Github here: https://github.com/jbryer/ShinyPoster. The template provides a framework to quickly build a poster in Shiny. The template utilizes the
navbarPage layout along with certain elements from the
shinydashboard package. This allows for multiple views of the poster. Additionally, there is a “View Full Screen” button provided in the top right corner (Tip: you can scale the web browser to fit the screen resolution).
To get started, modify key variables in the
global.R file, namely:
navbar_title– The content in the upper left hand side of the navbar.
poster_title– The title of the poster.
poster_authors– The poster’s author(s).
background_color– The background color of the poster.
tabs_with_white_background– Any tabs that should have a white background instead of
Additionally, any data should be loaded within the
global.R script and the
poster_data variable should be set to the
data.frame from which descriptive statistics are presented.
To get you started, there are six boxes to hold content across two rows where row one had three columns and row two had two columns. To simplify the process of populating content in your poster, the
includeMarkdown function is used with individual markdown files located in the
If you wish to use RMarkdown you can use the
renderRmd function (included in the
R/ direcotry). This requires two steps: 1. Create an object on the
output object that is the results of
renderRmd; 2. Use the
htmlOutput in the
ui.R script to include the output of the Rmarkdown file.
To leverage the interactive descriptive statistics set the
poster_data variable in
global.R to your data frame. There are functions in the
server.R that will create
ggplot2 figures for variables users select from your data frame. These are located on the “Desciptive Statistics” tab. If you wish to exclude this feature you can delete
tabPanel from the
I hope this framework is useful for those who are presenting an electronic academic poster. You can see a poster we created for AERA 2022 here: https://r.bryer.org/shiny/AERA2022/
R Core Team (2022). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.
Winston Chang, Joe Cheng, JJ Allaire, Carson Sievert, Barret Schloerke, Yihui Xie, Jeff Allen, Jonathan McPherson, Alan Dipert and Barbara Borges (2021). shiny: Web Application Framework for R. R package version 1.7.1. https://CRAN.R-project.org/package=shiny
Winston Chang and Barbara Borges Ribeiro (2021). shinydashboard: Create Dashboards with ‘Shiny’. R package version 0.7.2. https://CRAN.R-project.org/package=shinydashboard