Pointless Personal Data

This post isn’t about email. I’ve pretty much exhausted that topic for the moment and have completely ruined my reputation on campus as someone who is responsive and ready to help at the drop of an email. People have started emailing me to apologize for emailing me. Mission accomplished. That whole thread was more of a window into my soul than I expected. there’s one thing I didn’t mention. While writing those posts, I kept a spreadsheet of how many emails I sent and received from my work email account each day.

So, here’s another fun fact about me: I compulsively track pointless data about my daily life and habits.


I keep track of how often I have listened to every song in my iTunes library. I keep a spreadsheet listing the Top 15 songs played since 2006. The sheet is updated on the first day of every month. The top track (150 plays) is “Ruby Blue” by Roisin Murphy. “Ruby Blue” has been my most listened to track since January 2012 when it replaced Radiohead’s “Street Spirit” (112 plays).

I am on a mission to rate every song in my iTunes. This is an important project because it allows me to make the most of smart playlists. (Note: I’ll need to write an entirely separate post on smart playlists).

My monthly spreadsheet also includes my progress with this project. Of the 12,127 songs currently in my iTunes, 2328 are currently unrated. That’s 19.2%. I’ve been tracking this since June 2011. I figure I’ll be finished by this time next year.

To make my rating easier, I keep several smart playlists of unrated songs (alpha by album, alpha by song, jazz alpha by album, jazz alpha by song, classical alpha by album). Shocker: my monthly spreadsheet lists my progress by album and also by song. (By album: Lennon (Disc 2) by John Lennon; by song: Marble Halls by Enya). (Note: Enya is a yawn and this particular song will probably be a two star. My rating system is another entirely separate post for later.)

This isn’t as much work as it sounds. I don’t spend lots of time doing this, and it makes me happy. I don’t know why. I use to automate the process of tracking play frequencies by scrobbling my iTunes to Last.fm. They give lots of good data about frequency of plays segmented by week, month and year with a sub-sort by artist. Lots of fun until I noticed that the Last.fm database couldn’t disambiguate songs with the same title. I was listening to lots of Yo-Yo Ma and getting crazy high counts for Allemande and Courante which isn’t really a unique song title. Last.fm was collapsing every play for a song by that name into one entry. Major problem since each title occurs at least 7 times in my iTunes and each is a different song.


I have kept an Access database of every book I have read since May 2005. I haven’t updated in a little while since I post everything to GoodReads now. I need to go back and update the database. It gives me a nice report of every book read sorted by author.


I use the Run Keeper app to track my runs. This is great because it automates the collection of time, distance, pace and calories burned.

Calories and Weight

I use the Live Strong app to keep track of daily calorie intake and also track my weekly weight gains/losses. Super easy to use because it is backed by a database populated with common, name-brand foods with authenticated calorie values pre-entered. That’s all I’m going to say about that for right now.

Anyway, you get the point. I like to count things. I like to put things in a spreadsheet and keep track of them. I can’t say this makes me a better, more effective person. I also can’t tell you exactly why I’m doing this and what the specific appeal is for me.

Please tell me somebody else out there is a complete nut job about keeping track of the pointless, quantifiable minutia of everyday life. This blog is called Ubiquitous. Quotidian for a reason. File this one under Quotidian.

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