Experiencing Data

Data science is one of the big trends in pretty much every industry.

What is Data Science?

The term itself hasn’t even been around that long. Just a quick skim of the data science Wikipedia entry gives the distinct impression of both it’s short history and the somewhat flexible definition of the term, as it’s used interchangeably with things like business analytics or statistics. For instance, sometimes people say “data science” when they’re actually just using data. (One can’t help but be reminded of the way “user experience” is confused for “user interface design” and other pursuits.)

The best short definition I’ve found comes from an answer from a guy named Drew on a Quora thread called What is data science:

Data science most often refers to the tools and methods used to analyze large amounts of data. As such, the discipline is an amalgamation of many bits from other areas of research.

Whatever your definition, companies of all sizes are sure to continue to placing more and more value on data-driven decision making and others will continue to capitalize on the various forms of information collected via their various products and services. This is partly why Harvard Business Review called the Data Scientist role the “sexiest job of the 21st century.”

Data UX

For these reasons, I’m curious to learn more about how data can be experienced. Because actual data is, of course, pretty boring. If I think about raw data, I tend to envision a grey, monotonous spreadsheet with rows upon rows of numbers, along with really sad people whose job it is to aggregate and manage it all. :(

However, data can be both beautiful and incredibly useful—once it’s turned into something more human friendly.

These are a few examples I’ve noticed recently of data presented in a way that is easily consumable:

• FiveThirtyEight — Nate Silver’s famous polling aggregation and statistical analysis website makes some really awesome graphs. Many of these charts also come to life as you hover over them. Check out the presidential approval ratings or the graphs in this article about the Eagles for some good examples.
• Fitbit dashboard — I love the way Fitbit can take the data I give it with my wearable (as well as things I can input manually in the app, such as weight) and turn it into charts that are quickly understood and help me reach various goals.
• Spotify — You might not think of this as data visualization, per se, but all those playlists that show you your top songs for the year, the new music you might care about, and other personalized content are all using your data to then communicate something back to you. It just happens to be very focused. (You can see similar outputs with LinkedIn’s suggested connections, Facebook’s “on this day,” etc.)
• /r/dataisbeautiful — This subreddit is a great place to quickly see a lot of creative and effective charts and graphs. I like the channel’s description: “DataIsBeautiful is for visualizations that effectively convey information. Aesthetics are an important part of information visualization, but pretty pictures are not the aim of this subreddit.” If you want to learn something new in about 2 seconds, check out this graph about terrorism. (Then you can quickly skim the top comments for various perspectives, too.)
• “Washington, D.C. gives no f***s” — A deep dive on a very important issue, this Medium post analyzes cursing trends on Twitter.

What cool data visualizations have you seen lately?

Do you agree that UX pros need to be thinking about data more? What do you think UX students ought to be doing in order to get better at data visualization and data interface design?