Guiding Principles for Interactive Graphics Based on LIBD Data Science Projects

Abstract

Interactive graphics have become popular in media to provide a richer context in order to explain a set of observations. One of the most important components of any data science project is called exploratory data analysis. Interactive graphics have made their way from media into science and facilitate communicating results. There are many types of interactive graphics and some are easier to implement than others. At the Lieber Institute for Brain Development we have different types of data sets and have built interactive graphics to communicate our results to the scientific community and among ourselves. Two examples include the LIBD eQTL browser http://eqtl.brainseq.org/ which describes results from a genomic analysis and an internal Shiny application for our brain collection information. shinycsv is a public version of our Shiny application at can be accessed at https://jhubiostatistics.shinyapps.io/shinycsv/. Each tool serves a different purpose and it’s important to decide how much effort is needed to achieve the desired communication goal. We’ll describe the guiding principles we had building these tools that will help you to start using interactive graphics.

comments powered by Disqus