Data Design

By ian

I recently found the Feltron Report by way of Adaptive Path. It’s a report outlining Nicholas Felton’s activities this year, which is not a horribly engaging topic. However, I read through every page of the report. Feltron has taken mundane details about his life and made something that is quite nteresting.

Looking at this report, the engineer in me instantly started trying to analyze what made it so good. Of course, there is no single aspect that makes it good; its combination of good parts that come together to create something better. There are a few things that he does that I really like.

Intentionally Busy Visuals

The first page of the calendar is almost unreadable, but in a good way. The display on the left doesn’t work if it encourages you to look at individual days. Combined with the key in the top right, it provides a nice way to quickly see what happened when. By making the dates mostly the same, it makes variations in the dates (free & vacation) stand out. The busy background makes it interesting and difficult to read some individual dates, but doesn’t interfere with the ability to see groupings of free or vacation dates.

The large text in the background also serves as the page title. It’s nice because it still clearly conveys the page’s subject without taking up the top 20% of the page to do it. The only page it doesn’t work for me is the last page.

Intuitive Visualization

The graphics in the report are very intuitive. Eventhough they don’t really follow any specific conventions, its fairly easy to interpret the data. On the drinks page, you almost don’t need the small descriptive text. At this resolution, most of the descriptive text is still unreadable, but most of the trends still come across well. I can tell where Felton drinks, what his favorite drinks are and lots of other data without needing that detail information.

Overall, I think that this document is great. It really does a great job of showing how important data design is. Hopefully, I’ll be able to use this as inspiration to improve my own data design.