Interactive data visualization on the web using R

2016-12-12

Slides available at http://bit.ly/phd-seminar

This work is released under Creative Commons

Why interactive graphics?

Why interactive graphics for presentation?
- Enhances knowledge transfer (see New York Times)
Why interactive graphics for exploration?
- Identify structure that otherwise goes missing (Tukey 1972)
- Better understand/diagnose models (Wickham, Cook, & Hofmann 2015).
- Generate insights faster (iteration time is crucial!)

Why interactive graphics on the web?

Portable (i.e., cross-platform)
Simple to share
Encourages composability (i.e., reports, dashboards, etc)
Enables integration of multiple systems (1 + 1 > 2)

The problem with web graphics for data analytics

Great for conveying information (viz is known), but impractical for exploration (viz is unknown).

The reality: analysts have to learn/juggle many technologies.
My goal: An R interface that makes 80% of techniques seamless, quick, and easy (w/o knowledge of web technology).
My contribution: Designed and implemented a linked brushing framework.

Implemented as an R package