Quantified Self (QS) is a method of collecting and interpreting your personal data, usually for self improvement. The inputs range from health datapoints like sleep hours or running miles, to media consumption like movies watched or books read.
Luckily, I happen to hoard data and lots of it. I’ve done my darndest to Jaws-of-life this data away from corporate silos or simply start collecting it myself. For the most part this data is gathered automatically. There are others who opt for a richer, minute-to-minute, manual data point entry but I don’t think the tradeoff is worth it. Automation rules, manual life-logging drools.
I have broken down my QS project into two corresponding phases:
Step 1: Collect Step 2: Interpret Report improvement ideas Inspiring Links Inspiring quotes My latest report can be found here.
I take an overwhelming amount of inspiration from Julian’s media consumption reports.
Step 1: Collect A niche part of the internet has already trailblazed the collection of numerous health, emotion, and habit data.
This is a list of what I’m exporting and from where, along with what I’d like to add.
ListenBrainz and SimpleScrobbler for music listen history GPSLogger location tracking HoTS game history AntennaPod syncs to GPodder.net for podcast history Habits for custom streak tracking (meditation, exercise, mood, etc) Beancount for personal finance records Miniflux reading time New RSS subscriptions Dead links, with substitute links to my archive Inventory Updates Step 2: Interpret There’s so much we can learn about ourselves, if we take the time to look. Sometimes, our money knows us better than we know ourselves.
Tracking our finances can reveal what we are in denial of, […] and what might be holding us back.
Robert A. Belle
After beginning my data collection habits, I can focus on creating automatic reports of this data. These will aggregate statistics and hopefully help identify trends in my personal behavior.
Parsing of this data is done using my QS parsers.
Know your wolf.
Report improvement ideas Music Breakdown by hour, genre? Show map of artist location Yearly overviews with manual interpretations Redacted summaries of journal entries, like Julian’s digital playground. █████████ ████ ████████ ❌
Inspiring Links Visualization https://datasette.io/ https://github.com/heedy/heedy Tools and Data https://github.com/woop/awesome-quantified-self https://anaulin.org/blog/structured-book-data-in-hugo-posts/ Excellent Examples http://feltron.com/FAR14.html https://julian.digital/location/madrid/ https://szymonkaliski.com/stats/ Inspiring quotes “huh, I appear to netflix-binge under certain conditions, despite the fact that I’d rather not. I wonder which conditions, specifically, led to that binge! What were the triggers? How could they have been avoided? What methods might help me avoid binging in the future?”
to get anywhere I need to record how things felt in the past.