Among the lessons he said he learned about working with R to analyze this data:
- Use R Markdown to blend explanatory text with analysis and graphics. R Markdown "makes it super-amazingly awesomely easy to document, iterate, modify and share analyses," Rudis said.
- "Boil everything into packages," even internal analysis code you're not planning to share externally. This makes it easier to document functions and let others check your results.
- Version control such as git is "vital to survive everything."
Other open-source tools used in the project include GitLab for internal collaborative development and Slack for collaboration; Rudis wrote an R package called slackr to make it easy to send analysis from R directly into Slack.
Also used: SurveyGizmo, Room.co for secure video chats; Google Hangouts was a non-starter because Google records those sessions, he said, GPG Suite for encrypting communications and RStudio for working in R.
Rudis's slide presentation for the EARL Boston conference is available on Slideshare.
Sign up for Computerworld eNewsletters.