In order to get things done people need to communicate effectively. At school, teachers present to students. In consulting, consultants make powerpoint slide decks. In research, researchers make presentations and talks to spread their ideas.
When it comes to data scientists, many of us write code (in R, Python, Julia etc) in order to analyze data, inform decisions. To many people, what we do is rocket science.
What is the most effective and easy way to spread our ideas and grow impact? A good answer is interactive visualization. And not just for data scientists, but for anyone working with analytics.
Sure enough, pretty and intuitive graphics are a good way to deliver insight. And, with modern technologies interactive visualization can grow into products, viral marketing campaigns, and journalism pieces.
I have been doing interactive visualization for a while. Below is a visualization I made to explore geographic enrolment patterns of HarvardX. What started as an exploratory project ended up as a product -- an interactive analytics platform we called HarvardX Insights. It ended up on the cover of Campus Technology, and several universities from around the world contacted HarvardX to get the code.
And here is something for data scientists -- a visualization of the Hamiltonian Monte Carlo algorithm. I taught it to my students last year during a graduate course on statistical computing and interactive visualization at Harvard Statistics. This visualization was one of several I created for the course together with students.
People who work with data increasingly need to acquire and apply creative coding skills in order to put their ideas to work. This helps come closer to the end user of an analytic insight, and avoid possible operational distortions and dead ends along the way. That's why, resources that promote and teach creative coding are in high demand among my peer data scientists. I am a big fan of Mike Bostock's Blocks, and other resources such as Codepen, JSFiddle, and Stack Overflow.
Recently, I have been using and contributing to Databits more and more. Databits is a website for data scientists, data journalists, and other creative coders to share work, connect, and grow impact. I believe that eventually, the site will allow to be more targeted and specifically learn from and follow peer data scientists and other creative coders who are focused on producing effective interactive visualization and other cool stuff. For example, I look forward to learning some Processing applications from this guy. In the meanwhile, I helped put together a simple databit based on Processing.js:
The site also runs Challenges, an initiative aimed at finding meaningful problems for creative data scientists to solve, and put on their portfolios. I find this pretty cool.
I look forward to learning new things, finding cool problems, and making the world a better place with data. Now my creative work has a home -- you can check out my creative endeavors and interests on my Databits profile page.