I'm currently studying the MIT Big Data and Social Analytics class online. It's one of the collaborations GetSmarter has with the Massachusetts Institute of Technology, and takes the form of an 8-week, intensive, hands-on course that explores data and social analytics fundamentals.
I'm really enjoying the course, and one of the reasons is that our Learning Design team, together with our talented Head Tutor, chose to expose students to the underlying process of data analysis by using Jupyter notebooks. It's been a while since I last programmed, and it feels good to get into the detail of loading and manipulating data sets, producing useful visualisations of the data and answering interesting questions. Jupyter makes this very easy - even for someone who hasn't touched a line of code in 6 years, although there is certainly a learning curve that non-technical students need to push through.
Early on in the course, Professor Sandy Pentland introduced us to the value of one's personal location data. It is arguably the most valuable data we have - where are we right now, where have we been, what are our regular patterns of movement, what insights can we draw by analysing our location history, etc...?
Have you thought about how you could use, and how others currently are using your location data? If you have the Google app installed on your cellphone, chances are that they've been tracking and using your locations data for some time now. Facebook, Waze, Twitter, Pokemon GO (if that's your thing!) - all of these apps, and more, do their best to have you allow them to use your data. Oftentimes, by sharing this data you help them help you. For example, whenever I leave the office, Google tells me how long it will take in traffic to get home. That's very useful to me, and so I continue to let Google track my location. More recently, Facebook has started making friend requests based on who I've been in close proximity with. Another interesting use of my location data.
So, knowing that I've let Google track my data for some time now, I decided to explore my data by downloading all of it from the past few years from Google. It's really simple to do - just go to google.com/takeout. You'll get a zip file that contains a file named LocationHistory.json. That's the raw GPS locations with time stamps of where you've been.
I then uploaded this file to a free web-based visualisation tool called locationhistoryvisualizer.com/heatmap/. It's a super tool that shows your location data in a heatmap that allows you to zoom in and out to visualise your historical location data at any level of granularity.
Here's what my global heatmap looks like, using my location data from the past few years:
It's plain to see that I spend most of my time in Cape Town, South Africa, and some time in Johannesburg, United Kingdom, Southern Europe, and the East coast of the United States of America. The remaining purple smudges show I've spent time on holiday in a few other parts of the world too.
The first thing I did was take a closer look at where I spend most of my time: Cape Town, South Africa. Here's my location heat map in and around Cape Town:
We generally have a good sense for where we spend our time, right? We spend time at home, at work, at friends houses, with family, exercising, socialising, etc... And what I found so useful about reviewing the heatmaps, at many different levels of granularity, was that it gave me both summary and specific views of where I spend my time.
Obviously I spend time in and around my home. I lived in both Woodstock and Claremont while this data was collected, and this is obvious from the central red colour on the map. And I can see that I venture in to Cape Town CBD and to the Southern Suburbs, but not nearly as much as the time I spend in and around home and at work, which is in Observatory. I was surprised to see how much time I spend at the airport (red dot on right hand size of image), and I'm also surprised to see how much time I have spent in shopping malls (red dot at top of image). Lastly, as a trail runner I have spent a lot of time on Table Mountain, which is clear because the red colour eclipses the side of the mountain. When zooming into Table Mountain, I can see which trails I use most.
What interests me is that this data helps me confirm where I spend my time. That may sound like a silly thing to say, give that we all have a good sense for where we spend our time. But after exploring my location data, I learned a few things about my travel patterns, where I spend more time than I thought I did, and where I'm not spending any time at all. It can be said that analysing your historical location data is a way of reflecting on one's pattern of movement. Thoughtful reflection is an important tool for learning.
The potential to use our location data to improve our lives is immense. Researchers at MIT have found that once you know your regular pattern of movement, if you depart from that pattern of movement it can be an early indicator of illness. And by understanding your patterns of movement, and then finding other people who have similar patterns of movement, you can learn a lot about yourself and others based on these shared patterns of movement as you often share many of the same characteristics as those people who have similar patterns of movement to you. In fact, it's been shown that one can better predict someone's behaviour by understanding the behaviour of others who share their patterns of movement, than by using their own demographic detail.
Most importantly for me, reviewing my location data at an aggregate level is an opportunity for me to better understand myself. If you're interested in exploring your location data, start collecting it with the Google app and use a tool like locationhistoryvisualizer.com/heatmap/ to map and explore it.