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Comment by mg | Hacker News Reader

I have been doing "self-tracking without tools" for about two years now. I described my approach in this essay last year:

https://www.gibney.org/a_syntax_for_self-tracking

I can not see me ever going back to not doing this. It is just too interesting to be able to look up and analyze all the data of what I did and how I felt.

Additionally, it improved my ability to notice and quantitatively express what I feel.

My expectation is that in the future, this type of self-tracking will become very common. Not only for the sake of curiosity. I expect that it will also turn out useful to do "randomized controlled trials of one" which will result in meaningful results for the individual on how their behaviour impacts their mood and health.

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Does "analyze" in your case mean skimming through past events or something more involved, as in the Wolfram's article? I've been logging my video game and work sessions in a similar manner for ten years and always wanted to add a statistics report to the custom tool I use, but my ideas stop at simple stuff like longest N per period or bar chart distribution per period.

I started writing an analytics pipeline for this type of log about a year ago and worked on it on and off. Interestingly, it turned into something close to a jupyter notebook alternative that runs in the browser.

The part that is most tricky is to do treatment-effect analysis with this type of irregular data. I have written a module for it and it looks promising. For example: When first analyzed a ton of treatment-effect-pairs, the one that strongly stuck out is that Ibuprofen causes a drop in headaches :) A sign that the approach works. Among the promising relationships I see is that it looks like Vitamin D3 intake reduces symptoms of the common cold. I have found some of these "promising" pairs, but I need more data before I consider them relevant enough to publish them.

Very cool.

I feel like the pipeline of knowledge could do with more published lists of "promising pairs" that others could follow up on.

It will be an interesting data world when everything significant we do is auto logged, hopefully in personal private logs, by our smart watches or glasses or something. Seems inevitable.

Then we will finally find out if an apple a day really keeps the doctor away!

You might want to try org-mode

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