Run Maps - A first forey into Data Visualisation

BY: Saurav Dhungana
July 13, 2014 · 3 minute read

Mapping people’s running routes in Kathmandu and few other cities.

Having worked as an data analyst for more or less my entire professional career, I always knew that the successful communication of results is what defines the success or failure of an analytics project. Call it reporting, presentations, visualisations or any other term you like, it has to make sense to the end stakeholders. The reason being that they are mostly non-technical business people. So, as I embark on this journey of starting a data analytics company, I’ve decided to focus on the communication (or storytelling) part of the process from the very beginning. This also fits well with my design-first ethos.

Data Visualisation for me is - the method of plotting numeric data via graphs, charts and other visual aids. For most Microsoft Excel is the first thing that comes to mind when this term is mentioned. But I’ve always found it a little limiting. So, as I looked around for better ways to represent the results of our analytics projects. Turns out that there have been huge leaps lately with the type of visualisations one can create. If you’ve read the New York Times' coverage of the 2012 US election, or watched one of Hans Rosling's captivating talks, you’ve seen this first hand.

Insipred by the plethora of good visualisations online, I’ve taken it upon myself to learn how these are made. This doesn’t however entail merely learning some popular tools like R and d3.js. I want to learn to ask relevant questions in both business and social scenarios and enable myself to answer those through compelling, interactive visualisations.

One of the blogs that I’ve extensively follow is Nathan Yau’s Flowing Data. In one of his articles, Nathan showcases beautiful maps where he overlays gps routes of people’s runs in different cities around the world. I got really fascinated by this and had to make them myself.

After looking around the web, scraping some data and extending Nathan’s code, I managed to learn how to create them. I call them Run Maps, which is a term I borrowed from the internet. The first map I made was for my own city - Kathmandu.

Unfortunately, logging your runs on mobile apps (runkeeper in this case) doesn’t seem to be big here. There were only about 50 routes that I managed to scrape. I’ve tried to add my own asthetics. Also, for the ones you need some explanation, the thicker/brighter the line, the more popular the route.

Run Map of Kathmandu

The next one I made is another city where I’ve lived in the past - Helsinki. Thankfully, I managed to find over a 1000 routes there and it looks much better.

Run Map of Helsinki

Finally, I made one for San Diego as well. Though I’ve never been there, my company has our US offices there. So, it is a city important to me.

Run Map of San Diego

I’m very happy with the results. Not only have they turned out good, but I got a certain pleasure knowing that these maps depict the “running” pulse of the city. Who knows this may even inspire people to go for a run themselves, including myself.