The Quantified Self

I don’t know that I have all the pieces and parts of my own personal ‘quantified self’ arsenal fully deployed, but I’m a dedicated logger of workout data via RunKeeper.

The past week have seen the RunKeeper Health Graph API take off, the merger of Contagion Health and Health Month in to Habit Labs and my own discovery of the Quantified Self message boards.

Be still my beating heart.

Actually don’t.

Log those heartbeats for an activity graph for later insight mining.

I’m really only scratching the surface right now, barely using RunKeeper to log runs, elliptical workouts and the occasional weight lifting session. I wish I kept better notes, even if I didn’t publish them out to Twitter, Facebook or Dailymile.

I’m thinking of adding at least a FitBit to capture more data (sleep, mostly) but I’m more interested in novel ways to express that data visually so I can more easily understand fluctuations and trends.

One this is certain: I need to curtail my caffeine intake – currently one cup on weekdays, sometimes a cup on the weekends – because I feel as though my long runs are suffering. Sure would be nice to back up that claim with a chart.

Right now I’ve got the raw ingredients of a data cake when I’d really like to pig out at the trough of knowledge. Dig?

data cake
Image by EpicGraphic

I’m also preparing to run a half marathon later in the year. Either the Atlanta Half Marathon or the 13.1 Marathon Atlanta. The former has a course I’m more familiar with and would allow for more time to train, but it falls very near Thanksgiving. If I’m leaning one way or the other, I couldn’t tell you.

Maybe I’m just hoping some pertinent data point will leap out of the app or iPhone and tell me what I should do. It’s certainly “listening”, it might as well advise me too.

Either way, I really enjoy knowing I have the data even if I’m not utilizing it to it’s fullest potential.

I’ve been trying to weave all those GPS coordinates, speeds, paces and times into a story I’m writing about my experiences as a first-time runner. I’ve gotten some good parts written but, again, the manual notes I should’ve written just aren’t there and that’s more important – memory & sensation – for the writing process.

If anyone has any tips or tricks regarding how they use all their automatically-collected data, or any pointers for getting better at manually annotating data, I’m all ears.

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