Some people may be wondering how I find all the amazing people conducting neat self-tracking experiments and creating jaw-dropping personal data visualizations. Well, for the most part I just listen. I’m constantly paying attention to what’s being said on twitter about #QuantifiedSelf. When that doesn’t work I just use the power of Google to find people who are blogging about self-tracking, self-experimentation, or personal data. It’s great to look through the search results and see how many people are sharing their personal stories and insights. While doing some searching this morning I stumbled across a project that immediately brought a smile to my face. Hopefully you’re excited by this as much as I am.
Chris Volinsky is a statistician at AT&T Research and he’s no stranger to handling large data problems. Back in 2008 he was part of the team that won the $1 Million Netflix prize. He also has quite the impressive list of research papers that illustrate the many different uses of cellphone location data. But what is really interesting about Chris is his newest project: My Year of Data
Back in November of 2011 Chris started off a blog entry that with this:
My name is Chris. I am 40 years old. I am 5’9 1/2″ and weigh 174 pounds. I walked 9,048 steps and have consumed 1,406 calories today (so far).
Realizing that he’ld been gaining weight and wasn’t at his optimal health he decided to take a data-centric approach to improving his health. He is a statistician after all. So far, he’s found some interesting things. Take for instance his weight and dietary tracking.
As he explains in this post, Chris typically has a hard time tracking his diet consistently. This can be pretty frustrating when you hear about how important it is to eat this or not eat that to help with weight reduction. Rather than get frustrated Chris turned to the data to see what he could learn. When he stopped looking at the data he was entering and started looking at the missing data an interesting trend lept out. He found that fluctuations in his weight appeared to be correlated with whether or not he was logging food. Take for instance the plot below. It appears that there is a pretty clear association with periods of weight loss and periods of actively logging his food (pink zones). The opposite also appears to be true – no food logging = weight gain.
Weight chart with food tracking highlighted in pink
So this is where a typical NFATW post would stop. We have an interesting finding and a neat data visualization. But, Chris is doing something much more interesting than just talking about his weight data. He is on a long-term self-tracking and self-discovery journey and he is trying to enlist other interested parties to help him. Chris is going the extra step and posting all of his self-tracking data online for anyone to analyze, visualize, or just get inspired.
You can access all of his amazing data via a public dropbox folder that he’s set up. He even has a nice README file explaining the datasets and formats. So far he’s sharing the following:
- Fitbit: sleep and activity data
- FitLinxx: weight training data from gym activities
- Livestrong: dietary tracking data
- Runkeeper: running and other exercise activity data
- RescueTime: productivity tracking (computer/internet use)
All the data is open and available for you to play with. This should be a really interesting project to keep “track” of in the future (pun definitely intended). To help inspire some action on your part I took some time today and looked at Chris’s most recent available data to see what I could find out. I downloaded his Fitbit data and decided to look for any interesting patterns. Turns out that when taking a look at his daily patterns of activity there seems to be something going on on Thursdays that reduces his step count and activity time . Also, Saturday is by far the best day with an average of 9,862.56 steps and a 5.3 hours spent being active (data available here).
Mean steps per day
Mean activity minutes per day
Make sure to reach out to Chris over at his blog and take a took at his data to see what interesting thing you can figure out!
Every few weeks be on the lookout for new posts profiling interesting individuals and their data. If you have an interesting story or link to share leave a comment or contact the author here.