Katie Sasso
Data Scientist, Columbus Collaboratory
Published Aug 08, 2018

Two tutorials, 6 amazing keynotes, one trip to Australia, and tons of incredible talks, posters, and conversations later my second useR conference is a wrap. #useR2018 did not disappoint. In this post I want review my #useR2018 conference experience and just a few of the many aspects that made it so incredible.

The useR! Community

The magnetic environment that engulfs you as soon as you enter any useR conference is, perhaps, my favorite part. Brimming with passionate R programmers from a variety of backgrounds including academic and industry professionals alike, the useR community is diverse in more ways than one. I’ve never been to any other conference where I can dialogue with experts from such a wide variety of niche research areas on statistical and programmatic tactics that appeal to the boarder R community. This intellectual and cultural openness is the core of what makes the R community great. From the #Rladies community to the #useR code of conduct – the R community is committed to inclusivity. Steph de Silva spoke eloquently of this idea in her talk, and it is something that really hit home for me at this useR.

Personal Achievements

This was my first time presenting a main session talk at user! I had the privilege of presenting a super cool open source project The Collaboratory analytics team and I have been working on: using Electron to deploy R Shiny apps as standalone desktop executables. R Shiny allows R users to quickly build interactive dashboards for a variety of use cases (think of it as a super charged, fully customizable, and free, version of Tableau). Shiny is easy for R programmers to work with and a variety of deployment options exist; however, all of these options involve sending data and/or IP to the cloud and/or heavy IT involvement in order to stand up deployment infrastructure. My coworkers, Pete Gordon and Slava Nikitin, had the brilliant idea to package up R into Electron, in order to drastically increase speed and efficiency in deploying Shiny apps. With the adaptations made by the Collab team, our data scientists can now quickly package up anything built in R, from machine learning models to interactive visualizations, into an Electron-Shiny app and send then send the app to users as a standalone executable. The useR! crowd loved this idea just as much as we do! I was thrilled to give a talk on this topic to a packed room and to experience the adoption and collaboration of the open source community that followed. Since this time we have had 700+ views of our github repo, which contains everything users need to package up their Shiny apps as standalone executables. Super excited to see all the adoption and improvements to come to this project as we continue to work with R programmers from around the world (literally)!

Key Learnings

I wanted to share with you all just a few talks and tutorials that I found to be particularly informative. While I don’t have the character space to do all the great talks I saw justice, most talks and tutorials were recorded, so keep an eye out for them here. The #rstats community is also very active on Twitter, so check out the #useR2018 hashtag for highlights. For now, here are a few of my favorite talks: Fasster, mgcv, Code Smells and Feels, Beyond Syntax