When I was new to #dataviz, seeing only finalised projects by seasoned practitioners used to puzzle me: I always have thousands of questions on the process: how did you get there?
That’s why I document most of my projects, explaining the reasoning, design choices, technical hurdles etc.
Phew! I haven’t published any personal dataviz since IronViz; don’t get me wrong, I have plenty of ideas, but also plenty of work and a massive imposter syndrom to fight. I work well on deadlines, that’s why I entered the #Ironquest challenge of the month, which is around Viz a Year or Decade. I can’t say that I respected the theme fully, as I took a year going from oct 2020 to oct 2021, but I really wanted to tell a story about geocaching, so here we are.
#1 Getting the data
I wanted to automate as much as possible the process to extract my personal tracking data from Geocaching.com but the website doesn’t seem to allow webscraping; after a couple of hours searching, here is the current solution
Log in > Play > Search > Filter your search by ‘found by me’ > Add to a list > Go to your lists > download the GPX
But that’s not all! Then you need to install GSAK (Geocaching Swiss Army Knife), connect your login, upload your GPX. Why? Because I needed to look into the metadata, including distance from my home (and a bunch of other stats that I ended up keeping private). From there, you can export in an Excel format.
Fonts are Futura and Pompiere: Futura, because it’s sleak, legible, and the roundness echoes the bubbles shapes; Pompiere for its playfulness.
Made in Tableau. I’ve made some “simple but bold” moves in my dataviz design, including:
1/ a very simple lollipop chart: Ironquest probably deserves a dataviz with more wow effect; I tried for more complex charts (radial), but honestly, I don’t have the energy and I just wanted something that looked child-like because geocaching is a bit like a return to childhood
2/ a logarithmic scale on a bar chart that represents distance and no scale on my bar; 3 reasons to that:
- the variance between my local hunts (less than 5 km) to my furthest exploration (+2,000 km) was flattening 90% of my datapoints
- what matters is not so much the distance from home than the variance between the different distances
- Finally, we are talking self quantified data, not a business dashboard: we can live with a bit of approximation
As for dataviz inspiration, I Googled-images geocaching and search on Dribble and Behance… On the latter, I found Janelle Lim-Ranola‘s Geocaching Android App Redesign ; it inspired me the idea of a dotted line to guide the reader.
That’s all folks, any question or feedback, don’t hesitate!