Tag Archives: reading list

What We’re Reading

Ernesto is out for this round, so I’m filling in. I hope you enjoy this week’s list of articles, show&tells and visualizations!

Articles
“Standing Up for American Innovation and Your Privacy in the Digital Age” by Senator Ron Wyden. Access to your personal data is something that we care about and has been a topic of conversation at QS meetups and conferences. During Portland’s recent TechFestNW, Oregon Senator Ron Wyden took a strong stance on the nature of the relationship of the user and his/her data by criticizing the “Third-Party doctrine”.

Digital Health State of the Industry by MobileHealthNews.  In the hype-filled world of digital health, MobiHealthNews is one of the (few) sources we trust for business reports. Their latest quarterly roundup is very well done, as always.

Show&Tell
Better Living Through Data by James Davenport. James has over four years of battery log data from three laptops. By looking at the data, he saw a view of his own computer usage as well as a glimpse of his laptop’s secret life in the middle of the night. If you want to keep logs of your laptop’s battery, you can use the same script.

Visualizations
Which_Cities_Get_the_Most_Sleep__-_WSJ_com 2Which_Cities_Get_the_Most_Sleep__-_WSJ_com

Which Cities get the most sleep? by Stuart A. Thompson. We showed a visualization last week that used UP user data. This visualization is from the same dataset, but I couldn’t pass up showing it because the sleep/step pattern contrast between New York and Orlando is so interesting.

From the Forum
OPI TrueSense for Sleep Tracking
Report App Question
What is your opinion on neurofeedback?

This Week on Quantifiedself.com
Cors Brinkman: Lifelog as Self-Portrait
Eric Boyd: Tracking My Daily Rhythm With a Nike FuelBand
Kevin Krejci: An Update on Tracking Parkinson’s Disease
Mark Drangsholt: Deciphering My Brain Fog
Mark Leavitt: Whipping up My Willpower

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What We’re Reading

It’s a long one today, so buckle in and get ready for some great stuff!

Articles
The Quantified Self: Bringing Science into Everyday Life, One Measurement at a Time by Jessica Wilson. This piece, from the Science in Society Office at Northwestern University, explores the Quantified Self movement, with a particular focus on the local Chicago QS meetup. Always interesting to see how individuals draw distinctions between self-tracking projects and “real science.”

Diversity of Various Tech Companies By the Numbers by Nick Heer. Recently Apple released data about the diversity of their employee workforce. This marked the last major tech company to publish data about diversity. In this short post Nick takes that data and shows how it compares to data from the US Bureau of Labor Statistics. Interested in more than just the big six listed here? Check out this great site for more tech company diversity data (Hat tip to Mark Allen for finding that link!)

Intel Explores Wearables for Parkinson’s Research by Christina Farr, Reuters. Intel is in the news lately based on their interest in developing and using their technological prowess for qs-related activities. In this post/press release, they describe how they’re partnering with the Michael J. Fox Foundation to explore how they can use wearable devices to track and better understand patients with Parkinson’s Disease. It appears they’re also working to get their headphone heart rate tracking technology out to market.

Spying on Myself by Richard J. Anderson. I’m always interested in how people talk to themselves about self-tracking. This short essay describes the tools that Richard uses and why he continues or discontinues using them. His follow up is also a must read.

Dexcom Mac Dance by Kerri Sparling. You know we’re fascinated by the techniques and tools developed and refined by the the diabetes community. In this short post, Kerri highlights the work of Brian Bosh, who developed a Chrome extension to access and download data from Dexcom continuous glucose monitors on a Mac. (Bonus link: Listen to Chris Snider’s great podcast episode where he talks to John Costik, one of the originators of the CGM in the Cloud/Nightscout project.)

Show&Tell
The Three-Year Long Time Tracking Experiment by Lighton Phiri. Lighton is a graduate student at the University of Capetown. In 2011 he became curious about how he was spending his time. After installing a time-tracking tool on his various computers, he started gathering data. Recently, after 3 years of tracking, he downloaded and analyzed his data. Read this excellent post to find out what he learned.

Experimenting with Sleep by Gwern. One of our favorite self-experimenters is back with some more detailed analysis of his various sleep tracking experiments. Read on to see what he learned about how caffeine pills, alcohol, bedtime, and wake uptime affects his sleep.

QS Bits and Bobs by Adam Johnson. Adam gave talk at a recent QS Oxford Meetup about his lifelogging and self-tracking, his custom tools for importing data to his calendar, and what he’s learned from his experiences. Make sure to also check out the neat tool he’s developed to log events to Google Calendar.

Visualizations

NikeFibers
FuelBand Fibers by Variable. A design team was given Nike FuelBand data from seven different runners and created this interesting visualization of their daily activity.

SleepWork
I don’t Sleep That Well: A Year of Logging When I Sleep and When I’m at Work by Reddit user mvuljlst. Posting on the r/dataisbeautiful subreddit, this user tracked a year of their sleep and location data using Sleepbot and Moves. If you have similar data and are interested in exploring your own visualization the code is also available.

JawboneCity
In the City that We Love by Brian Wilt/Jawbone. The data science team at Jawbone continues to impress with their production of meaningful and interesting data visualizations based on data from UP users. In this post and corresponding visualizations they explore the daily patterns of people from around the world. Make sure to read the technical notes!

From the Forum
Export Moves Data to Day One
Understanding Patents – All your transmission data belong to us
Quantified Self, It’s Benefits
Sun Exposure and Vitamin D Levels Wearable Tracker

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What We Are Reading

We’ve compiled quite the variety of articles and links for you. Make sure to check out the show&tell and visualization sections below for some great Quantified Self examples. Enjoy!

Articles & Posts
To lead off today’s list I’m including two great posts from attendees at our recent 2014 QS Europe Conference. You can read more attendee recaps over onour roundup post.

Ten Things I Learned at the 2014 Quantified Self Europe Conference by Bob Troia. Bob takes a look back at the conference and describes his experience.

Quantified Self and Philosophy at #QSEU14 by Kitty Ireland. We hosted over 36 breakout discussion at our recent European Conference. In this post, Kitty describes one of the “standout sessions” that she attended.

Okay, back to list!

Wearable Computers Will Transform Language by Ariel Bleicher. This is a long piece, full of excellent examples of how personal personal computing is becoming, but my favorite leads the article. Wearable computers in 1961. Who knew!

CyclePhilly hopes to record biking patterns to help plan bike lanes by Jim Smiley. A big theme of our discussions at various QS events this year has been around the social and public good the personal data can do. This project, led by Corey Acri and Code for Philly, hopes to better understand where commuters are actually riding their bikes. This also reminded me of a recent data sharing deal between Strava (a GPS activity tracking app) and the Oregon Department of Transportation.

How Much Can We Demand of Consumer Connected Health? by Joseph Kvedar. We’ve mentioned this before on both the QS blog and in the reading list, self-tracking device accuracy is a tricky concept. In this short post Dr. Kvedar describes his experiences and some results using consumer tools in a clinical setting.

In-Depth: How Patient Generated Health Data is Evolving Into one of Healthcare’s Biggest Trends by MobiHealthNews. This is a nice long piece covering many aspects of the growing role of different types of health data in healthcare. I personally enjoyed learning more about the challenge of combining patient reported data with electronic medical records.

Show&Tell
Treadmill Effect of Spaced Repetition Performance by Gwern. In this exhaustive examination, our friend Gwern decided to test whether walking on a treadmill helped his memory. Specifically he randomized if practiced his spaced repetition while walking at his treadmill desk or sitting down and then looked at his grades (flashcards remembered correctly). You’ll have to read it to see what he foun. (Make sure to check out his other experiments as well!)

My Sleep Cycle Experiment and What to Limit Before Bed by Greg Blome. This is a great breakdown of what Greg found out about what affects his sleep by tracking 150 nights of sleep with the Sleep Cycle app.

Learning Ancient Egyptian in an Hour Per Week with Beeminder by Eric Kidd. Here at QS Labs we have a soft spot for spaced repetition (See Gary Wolf’s great primer here). This post details how Eric learned how to read Egyptian hieroglyphs using spaced repetition and Beeminder.

Visualizations
OpenVis Conference. Here you’ll find 18 great presentations by leading data visualization experts. Hard to pick a favorite, but I found Andy Kirks, The Design of Nothing: Null, Zero, Blank to be fascinating.

RunkeeperBreezeBreeze Habits by Runkeeper. The data science team at Runkeeper took a look at 75,000 worldwide Breeze App users to see what countries were getting up earlier, going to sleep later, and getting the most steps. I can’t wait to see more visualizations like this from Runkeeper.

 

 

 

Tableau Quantified Self Viz Contest. We mentioned this is last week’s reading list and the contest has is now over and we get to peruse the great entries. I’m going to include some of my favorites below, but make sure to check out all of them at the link above. You can also view the winners here.

spanglerThe Life of Spangler by Russell Spangler. Russell tracked his time for the month of April and presents the results.

 

 

 

 

rundergroundRunderground by Carl Allchin. Have you ever wondered if it’s faster to run than take the tube in London? Carl has your answer.

 

 

 

 

beatingdiabetesBeating Diabetes by Andre Argenton. Andre accessed the data in his Dexcom continuous glucose monitor and visualized it alongside data from his OmniPod insulin pump.

 

 

 

From The Forum
Measuring Cognitive Perormance

How To Track Smoking

Quantified Self Reading List (books)

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