The path was humbling, the path was steep, the path was sometimes so obscure that I wasn’t sure I knew the way. But earlier this summer, my first scratch-built digital research project went live on the shinyapps.io hosting platform. Written almost entirely in the R markdown programming language, A Visual Guide to Some Nineteenth-Century Composers and Their Publishers takes a quantitative look at the economic relationships that helped
nine ten prominent composers to get their music into print during the long nineteenth century. You can go behind the scenes and view the code for the entire project here on GitHub.
I came to R only after having concluded that none of the more user-friendly, prepackaged software options could offer precisely the combination of features and customizability that I had in mind for the project. Even with a series of handy R cheat sheets scattered around my desk, the process certainly took longer than the prepackaged route. But I’d like to think that much of the time spent importing the data, writing the scripts, and (inevitably) troubleshooting the resulting website will pay me back with interest as I embark on other R-based projects in the future.
That said, I wouldn’t have had the confidence to embark on even one R-based project without the encouragement of Rachel Starry, formerly of the University at Buffalo Libraries, who (to her credit) led me to believe that R wasn’t as complicated as it looked. Well, I’m glad that I took the bait. Now at UC Riverside, Rachel actually gave my project a shoutout in an “Introduction to Data Visualization” workshop that she conducted virtually on August 19, 2020. Slide over to around 48:30 in the YouTube video below: