The document provides an overview of the Quantified Self movement, detailing its origins, current tools, and trends in self-tracking. It discusses various methods of tracking personal data across different aspects of life, including activity, sleep, and mood, and emphasizes the shift towards passive data collection. The future of Quantified Self includes improving data portability, DIY data science, and encouraging individuals to reflect on their data to gain insights.

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

17. What are people using / Tools

18. Notable Tools
• Activity / general purpose trackers

19. Notable Tools
• Sleep specific tools

20. Notable Tools
• Brain activity / focus

21. Notable tools
• Genetic sequencing

22. Notable Tools
• Aggregators – will see more emerge

23. Notable Tools
• Mood

24. Notable Tools
• Food / diet

25. Notable Tools
Effect of Google Glasses and effortless data
Collection

26. 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.

27. 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

28. 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

29. 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

30. …what do you want to find out?