Quantified Self: A Guide to Tools, Trends, and Applications

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This is a presentation I gave for a class I taught at NYU ITP (Interactive Telecommunications Program) as part of their 2013 Summer Fellow program.

This is a presentation I gave for a class I taught at NYU ITP (Interactive Telecommunications Program) as part of their 2013 Summer Fellow program.

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  • Why > How > What
  • -Dozens of Meetups-Thousands of members-Massive recent press-Rapidly changing technology forcing continual re-examination of the scope

Transcript

  • 1. Quantified Self A Guide to Tools, Trends, and Applications NYU ITP June 7, 2013 by @andrewcpaulus
  • 2. Who I am and why I’m here -Product based startup background: Savored  Groupon  Basno -Co-Organizer of the NY Quantified Self Group -Experience with a variety of QS tools -Excited about helping people better understand themselves and empower them with useful tools
  • 3. What I have tracked • Activity – Jawbone Up, Moves, Chronos, friend’s app (mostly passive) • Sleep – Jawbone Up(mostly passive) • Mood – Jawbone Up (mostly passive) • Diet – Used personal notebook (discontinued) • Weight & fat mass – Withings Smart Body Scale (daily) • Heart rate – Withings Smart Body Scale (daily) • Productivity/computer usage – RescueTime (passive) • Location – Moves, Openpaths (passive) • Meditation time – Insight Timer (passive) • Clothing choices relative to weather – Personal GoogleDoc (discontinued) • Finances – Mint, Simple (weekly) • Goals – Weekly updated GoogleDoc (weekly) • Life balance & tasks – Color coded Trello board w/ weekly check-ins (daily/weekly)
  • 4. Activity and Sleep
  • 5. Weight, fat mass, heart rate
  • 6. Meditation log
  • 7. Productivity
  • 8. Agenda • What is Quantified Self • How quantified self got started • The state of quantified self today • Tools & apps • Trends • Hacking your own QS tools and projects
  • 9. What Is The Quantified Self? Original definition: self knowledge through numbers • Recently it has been a catch-all term in the media for anything where information relevant to an individual is tracked • At its core QS is curious introspection about the self as well as the methods and meaning of self tracking
  • 10. Image by whitney erin boesel for Cyborgology
  • 11. How it began First QS Meetup at Kevin Kelly’s house in September 2007 (image credit: Kevin Kelly) A sample of Tim Ferriss’s notes from the first QS Meetup (image credit: Tim Ferriss) The meetup initially just provided a forum for discussing the self-tracking that people were already doing
  • 12. Quantified Self Today
  • 13. QS Survey • Demographics & Basics – Age distribution - Average age = 36.2 years old, youngest = 23 years old, oldest = 74 years old – Gender distribution - 67% male / 33% female – Currently working in a QS related company or have created a QS tool – 30% • Data Sharing – % that share data with someone else - 51% – % that share data with a spouse/partner - 39% – % that share data with a health professional - 14%
  • 14. QS Survey
  • 15. What are people using / Tools
  • 16. Notable Tools • Activity / general purpose trackers
  • 17. Notable Tools • Sleep specific tools
  • 18. Notable Tools • Brain activity / focus
  • 19. Notable tools • Genetic sequencing
  • 20. Notable Tools • Aggregators – will see more emerge
  • 21. Notable Tools • Mood
  • 22. Notable Tools • Food / diet
  • 23. Notable Tools Effect of Google Glasses and effortless data Collection
  • 24. What do we do with all this? The QS world Gary Wolf would like to live in: • Data can be exported from the various systems we use into a simple format for exploration. • We can store and backup our data using whatever method we want. • We can share our data with whomever we want. • We can rescind permission to look at our data. • We can flow our data into diverse visualization templates and analytical systems.
  • 25. Where is QS going? • Moving from manual data entry to passive data collection will continue to bring it into the mainstream as tech improves • Brave vs. reckless with new technology, its methods and meaning • Increasing pressure to make data standardized, exportable, user owned • Boom of DIY data science
  • 26. What can you do / hack yourself • Typically useful to start with a hypothesis or a question/problem you really care about since most tech still requires some effort • There are tools for everything, just start tracking and iterate as you reflect on the data • Look for interesting combinations – Weight and Foursquare check-ins – Meditation time and mood – Sleep and productivity – Sleep and activity – Exercise and productivity – Key is to stick with it and standardize your data collection methods
  • 27. More personal hacking tools • Don’t be afraid of starting with a basic spreadsheet • Look for tools that allow you to export your data • Consider leveraging IFTT to automate data entry
  • 28. …what do you want to find out?