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TL;DR
Run shiny::runGitHub('jbryer/ShinyPoster') see an example poster.
Go to https://github.com/jbryer/ShinyPoster to download the template
Introduction
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.
Getting Started
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).
Global Settings
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 ofbackground_color.
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.
Poster Boxes
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 docs/ folder.
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.
Descriptive Statistics
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 ui.R file.
Conclusion
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/
References
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
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