Fitbit, you know I love you and you’ll always have a special place in my pocket.  But now I have to make room for the Moves app to play a special role in my capture-the-moment-with-data existence.

Moves is an ios7 app that is free.  It eats up some extra battery power and in exchange records your location and merges this with various databases and syncs it up to other databases and produces some very nice “story lines” that remind you about the day you had and, as a bonus, can motivate you to improved your activity levels.  I’ve attached two example storylines that do not make it too embarrassingly clear how little exercise I have been getting. (I have what I can consider legitimate excuses, and once I get the dataset downloaded, maybe I’ll add them as covariates.)  One of the timelines is from a day that included an evening trip to Disneyland. The other is a Saturday spent running errands and capped with dinner at a friend’s.  Its pretty easy to tell which day is which.


But there’s more.  Moves has an API, thus allowing developers to tap into their datastream to create apps.  There’s an app that exports the data for you (although I haven’t really had success with it yet) and several that create journals based on your Moves data.  You can also merge Foursquare, Twitter, and all the usual suspects.

I think it might be fun to have students discuss how one could go from the data Moves collects to creating the storylines it makes.  For instance, how does it know I’m in a car, and not just a very fast runner?  Actually, given LA traffic, a better question is how it knows I’m stuck in traffic and not just strolling down the freeway at a leisurely pace? (Answering these questions requires another type of inference than what we normally teach in statistics. )  Besides journals, what apps might they create with these data and what additional data would they need?