I enrolled in this class frustrated with my previous attempts to learn about data and visualization, and with a sense that, as a journalist to whom data is important to be able to understand and work with, I was missing something. While data still isn’t as intuitive to me as I would hope, I learned some important things this semester that will inform the way I look at, and work with, data in the future. They include:
- D3 is amazingly powerful. As my Phase I project tested the limits of my very limited coding skills, I abandoned D3 in favor of a more arduous method of visualization for my final presentation. But boy did I miss it while I was hand-drawing the tint masks and captions on my 360 video. The most exciting part of studying D3 was reading about and seeing examples of its ability to process large amounts of data, and change in response to the data that’s inputted. I got to experience this for myself on a basic level, and it was thrilling.
- Some of the best data visualizations are also the simplest. I wrote about this in my very first blog post, reflecting on one group’s ability to prototype a clear visualization of the different areas of study represented in our class, as opposed to my group’s far more complex, and messy, visualization of nationality and food preference. I’m still struggling with the principles of good, clear design when it comes to data, and I’ll be interested to hear my classmates’ reaction to my final project: is it fun and engaging, or do the bells and whistles take away from it?
So yes, I’m still not a data wiz, and I’m aware that my abilities are far exceeded by many of my classmates. Still, I’m leaving this class much more conversant in the norms and aims of data visualization, which, for someone who’s not aiming to become a data scientist, or even a data journalist, is enough for me!