Topic Archives: What We’re Reading

What We Are Reading

We’re back with another great set of articles, show&tells, and visualizations for you.

Articles
How to Make Government Data Sites Better by Nathan Yau. Government entities are some of the largest holders of interesting data. Nathan focuses this article on the difficulties of accessing and making sense of data from the United States Centers for Disease Control and offers some good ideas on how to make it better.

Project Eavesdrop: An Experiment At Monitoring My Home Office by Steve Henn. What happens when you start monitoring yourself in the same manner the NSA might be doing? The author employs some technical help to learn what data leaks are possible and what you can figure out from your digital trails.

Sitting is Bad for You. So I Stopped. For a Whole Month. by Dan Kols. As a past frequent user of a treadmill desk and a sedentary behavior researcher I found this article intriguing. Yes, a bit silly in nature, but an interesting look at what happens when you go to the extreme. I especially enjoyed the integration of personal tracking in the piece.

The Future of Biosensing Wearables by Rock Health. Our friends at Rock Health did some great research on where personal sensing is going.

Show&Tell
Analyzing Squash Performance Using Fitbit by Ben Sidders. Ben sought out to see if he could learn anything from his step data to improve his squash playing. In this post he explains how he used R to access his data and plot it against his squash records, which he also records.

My Life As Seen Through Fitbit. Reddit user, VisionsofStigma, plots a year and a half of Fitbit data to find out what is related to the rise and fall of his activity.

Visualizations
histogramFitbitFreeing My Fitbit Data by Bonnie Barrilleaux. Bonnie used our instructions for accessing Fitbit data in Google Spreadsheets then used Python to visualize her data. I especially like the histogram pictured at left. If you want to visualize your Fitbit data, she’s included her code in the post.

 

 

 

diurnalFitbitDiurnal Plot of Fitbit Data by Matthew Gaudet. Matthew was inspired by the diurnal plots from Stephen Wolfram’s in-depth personal data review. He implemented the same methods to better understand his activity.

 

 

 

iconHistoryIconic History by Shan Huang. As part of a the Interactive and Computational Design class at Carnegie Mellon University, Shan created a Chrome browser extension that visualizes your browser history. More about the project here.

 

 

 

lastfmAlbumsVisualizing Last.fm History by Andy Cotgreave. Andy has been using Last.fm since 2006 to track his music listening activity. As a data scientist he was interested in what he could learned from all that data. In this four-part series, he explores his data along side data from eight of his friends. (If you want explore your Last.fm data you can export it using this awesome CSV export tool.)

 

 

From the Forum
23andMe Data Analysis Tools

Track Your Phone Addiction

Just Want To Track Hours in Bed

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What We Are Reading

A bit of a change this week. Today we’re posting some of our favorite academic and scholarly articles dealing with many different aspects of Quantified Self tools and methods. If that’s not for you, make sure to scroll down for some great self -tracking projects and visualizations. (Make sure to click [pdf] for the full article.)

Articles
Understanding Physical Activity through 3D Printed Material Artifacts [pdf] by Rohit Khot, Larissa Hjorth, and Florian Mueller. A fascinating paper on what happens when you transform digital physical activity data into representative physical objects.

Personal Tracking as Lived Informatics [pdf] by John Rooksby, Mattias Rost, Alistair Morrison and Matthew Chalmers. The authors of this research paper interviewed users of self-tracking tools to better understand how they incorporate personal data into their lives. From the abstract, “We suggest there will be difficulties in personal informatics if we ignore the way that personal tracking is enmeshed with everyday life and people’s outlook on their future.”

Persuasive Technology in the Real World: A Study of Long-term Use of Activity Sensing Devices for Fitness [pdf] by Thomas Fritz , Elaine M. Huang, Gail C. Murphy and Thomas Zimmermann. The authors of this study interviewed thirty individuals who had been using different activity tracking tools for different amounts of time (3-54 months). Those interviews unearthed some of the reasons why people starting using and continue to find activity trackers useful in their lives.

Using MapMyFitness to Place Physical Activity into Neighborhood Context by Jana Hirsch, Peter James, Jamaica Robinson et al. What can you find out about a population by partnering with a QS toolmaker? Jana Hirsch and colleagues tried to answer that question by partnering with MapMyFitness to better understand where and how individuals in Winston-Salem, North Carolina were exercising.

Visualized and Interacted Life: Personal Analytics and Engagement With Data Doubles [pdf] by Minna Ruckentstein. Don’t let the the title fool you, this article is not about new analytical methods for personal data. Rather, it is an thorough examination of the phenomenology of self-tracking and how people construct understanding of themselves through personal data collection.

Show&Tell
Stress Trigger Personal Survey by Paul LaFontaine. We were lucky to hear about Paul’s stress tracking at the 2014 QS Europe Conference. While we work on getting that talk edited and posted online we thought this would be a great sneak preview.

Data, Pictures, and Progress by Chris Angel. Chris found out about QS while he was thinking about figuring out how to best lose weight. This post is his “first quarter” report from 2014.

Google has most of my email because if has all of yours by Benjamin Mako Hill. Benjamin has been running his own email server for 15 years. After a conversation with a friend he began wondering about how much email Google has a copy of. What followed was an amazingly in-depth analysis.

Visualizations
visualoop3030 Examples of the Art of Mapping Personal Habits. Some amazing examples of visualizations based on self-collected data in this post by Visualoop.com.

 

 

 

 

stravaheatmapStrava Labs Global Heatmap. You can explore over 220 billion data points from almost 100 million different running and cycling activities tracked with the Strava app. (If you’re interested in the engineering side of this visualization they’ve written a great blog post here.)

 

 

 

From the Forum

iPhone Equivalent of Android’s TapLog?

Breakout: QS and Philosophy

Method for Tracking “As Needed” Medications?

Advice on Apps Combinational

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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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What We Are Reading

Another long list of interesting stuff we’ve been reading this week. Enjoy!

Articles and Posts
Pilot at Boston’s Beth Israel Deaconess gives patients electronic access to therapists’ notes by Lena H. Sun. Should patients be able to read their therapist’s notes? A hospital in Boston is experimenting with that idea. This work was inspired by a project from our friends at the Robert Wood Johnson Foundation called Open Notes.

What If Our Refrigerators Get A Little Too Smart? by Owen Thomas. Are we setting up ourselves for a algorithmic controlled future of connected systems? Owen Thomas paints a slightly disturbing picture here in just a few sentences. (If someone writes a utopian rebuttal I would love to hear it.)

Google vs. our humanity: How the emerging “Internet of Things” is turning us into robots by Evan Selinger. Another nice piece on the ever increasing role algorithms have in our lives. I found the article well researched and full of interesting examples, least of not is the delegation of works onto wedding planners. (I was also tickled to learn that the chief economist at Google is named Hal.)

The United States of Metrics by Bruce Feiler. Apparently negativity is a theme this week. In this piece the author attempts to make the case that in using data to track understand your life, you are giving up the essence of life itself:

“Big Brother isn’t our big enemy anymore. It’s Big Self. That hovering eye in the sky watching every move you make: It’s you.”

The United States of Metrics isn’t such a bad thing by Nathan Yau. A short but great rebuttal to to the perceived grouchiness in Bruce Feiler’s piece mentioned above.

Here’s how I see it: I strongly believe in going with your gut instincts. It’s led me in the right direction more often than not. But, sometimes I move in the wrong direction, or I don’t know enough about a subject and all I have is uncertainty. If there’s data there to help then all the better.

Personal data and the quantified self – things you ought to know by Vicky Sargent. This is a nice review of the book, Hacking H(app)iness, by John C. Havens, which in part details how Quantified Self and tracking can influence happiness and mental wellbeing. (Editors note: A short book review of Hacking Happiness is forthcoming in a future What We’re Reading post.)

Data Ethic Workshop. Not an article, but a call for participation at a workshop on data ethics at the International Conference on Knowledge Discovery and Data Mining. Definitely something I’ll be keeping my eye on and will post papers as they become available.

What the Right Dashboard Can Do For Your Data by Thursday Bram. A nice overview of some available data dashboard systems and how dashboards can be useful for understanding multiple streams of personal data.

Show&Tell
A Look at a Few Months of HR and HRV Measurements by Marco Altini. Marco explains how he tracked his heart rate and heart rate variability while preparing for a half marathon and what he learned after 3 months of data collection. Take the time to read through this excellent post. It is really worth your while.

100 Blocks – A ‘Quantified Self’ Random Walk Experiment by Peter Gilks. Inspired by the mathematical concept of a Random Walk, Peter set out with his wife to let chance direct a 6-hour journey in New York City. Tracking all the way.

Quantified Jewel by Jewel Loree. Jewel has been tracking her music listening with Last.fm for years. After showing her pattern of music profiles to a colleague she was inspired to start looking deeper to answer an intriguing question, “What was I listening to sadder music every couple of weeks?”

Visualizations
Tablea’s Quantified Self Viz Contest. Notice anything about a few of those Show&Tell links above? They’re using Tableau as a their visualization platform. Tableau is hosting a Quantified Self Visualization contest. If you have some tracking data and want to share a unique visualization then you enter this contest and you just might win a chance to attend their annual conference. Contest ends May 26th.

percentfeedbackPercentile Feedback by Noah Slater. This is actually a combination visualization and tracking tool. Based on the great work of our dearly missed friend, Seth Roberts, and adaptations by Nick Winter, Noah has created a nice open-source project so you can experiment with Percentile Feedback. (Watch this talk by Nick to learn how he uses Percentile Feedback for productivity.)

 

 

UjiUji Wall Clock. This arcticle and interview with Ivor Williams explains why he built a clock who’s hands move to an individual’s heart rate. You can also see a video of the clock “in motion” here.

 

 

 

SC_kineticfrequencyKinetic Frequency. I’m a big fan of Stephen Cartwright’s work around designing physical installations that feed on location data. This new work uses color and and a 10×10 grid of movable columns to “display an infinite number of topographies based on a wide variety of inputted data.”

 

 

 

From the Forum

Best Pulse Oximeter for All-Night Logging?

Physical/Blood Work?

Breakout: Aggregator platforms: Understanding data?

Where Do You Keep Your Version of MyLifeBits?

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What We Are Reading

Enjoy these links, posts, and articles from around the web.

Health Care Apps Offer Patients an Active Role by Ann Carrns. A nice overview of different DIY health apps and connected home medical devices.

Getting the most out of RescueTime for your Quantified Self projects by Robby Macdonell. If you’re using RescueTime to track your computer use and productivity there are many options for extending the built in data analysis. This great post by Robby, who spoke about tracking his productivity at our 2013 Global Conference, showcases a few different methods. If you use one to look at your own data let us know in the comments or on the forum.

Downloading Your Email Metadata by Nathan Yau. Another nice how-to post from Nathan on FlowingData.com. Email is an area of rich information and most of time that data is left in the vaults of our email providers. This tutorial provides a great instruction set for gathering that data using Python.

20 Day Stranger by Playful Systems and the Center at MIT. An interesting project that will sync self-tracking data with a stranger for 20 days. It’s not in production yet, but you can apply to be a part of their trial. I’m really intrigued by the idea of sharing anonymously with strangers and what you might be able to learn about another person.

Spurious Correlations, Quantified Self, and the Health Care System by Martin Spindler. Do steps calculated, counted, and correlated by the smart pedometers of today actually improve lives?

Meet the Godfather of Wearables by Maria Konnikova. A really nice long read biographic piece on Alex “Sandy” Pentland. Sandy is responsible for running one of the most innovating research and design labs at MIT. Chances are that if you’re reading this then you’ve interacted with some bit of technology that originated with Sandy and his students.

Show & Tell

Fixing Sleep with Low Blue Light. This simple, but fantastic explanation of how one individual moved up his waking time by reducing his exposure to blue light.

Quantified Self: Three Months Later by Adam Sigel. This is a nice post about how different apps and tools helped Adam engage with his health and learn more about his life.

Visualizations

EdwardSnowVisualizing Zero: How to Show Something with Nothing by Andy Kirk. We’ve had some great discussions at recent Bay Area QS Meetups about the meaning of missing data. This short piece has some great examples of how the absence of data can be an important part of the story.

 

 

MoodMapMood Maps by Erin Hedrington. Some beautiful quantified self artwork here by Erin.

 

 

 

 

DataCrystalsWorld Data Crystals by Scott Kildall. Scott takes data sets and turns them into 3D printed representations.

 

 

 

 

From the Forum

Indoor Air Quality Monitoring

Discreet Stress Monitoring in Real Time

Inside Tracker Review

Which Wearables Have CSV Export

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What We Are Reading

Enjoy these articles, posts, and ideas from around the web.

Articles & Posts
Eight (No Nine!) Problems With Big Data by Gary Marcus and Ernest Davis. This is a nice short piece about what “Big Data” can and cannot do. Definitely a great reference to have on hand when you’re exploring your own data, or the data of others.

Wearables Versus There-ables by Naveen Selvadurai. I always enjoy reading what Naveen is thinking about in the personal technology space. He always does a great job of explaining his rationale and this piece is no different. Are we heading towards commodity sensors and more powerful stationary sensing systems? It’s an interesting idea.

Abandon All Hope, Ye Who Enter Dates in Excel by Kara Woo. Time and time again time/date formats show themselves to be the bane of every developer working with timestamped data. If you’re working in Excel with date dependent data this is a must read.

To quote John Machin, “In reality, there are no such things [as dates in Excel spreadsheets]. What you have are floating point numbers and pious hope.”

Sensor-Embedded Teeth for Oral Activity Recognition by Cheng-Yuan, Yen-Chang Chen, Wei-Ju Chen, Polly Huang and Hao-hua Chu. It turns out that every mouth movement you make (chewing, speaking, coughing, etc.) causes you teeth to move in different patterns. These researchers developed a small accelerometer-based sensor in an artificial tooth and were able to accurately capture different oral behaviors. A peak into our future?

Big Data and Its Exclusions by Jonas Lerman. Another “Big Data” themed essay in this weeks’ list. However this essay takes on something we’ve been hearing about more and more lately. If data is part of our future for determining public policy are there people that are missing in our datasets?

[...] big data has the potential to solidify existing inequalities and stratifications and to create new ones. It could restructure societies so that the only people who matter—quite literally the only ones who count—are those who regularly contribute to the right data flows.

How I Hacked My Best Friend’s Genome – And Could Hack Yours Too by Sharen Moelem. First, I don’t think “hack” is the right term here. I would prefer the title, “How I acquired my friend’s genetic information and had it tested.” Regardless, this short piece makes the case for understanding the legal protections, and lack thereof, of personal genetic testing.

Show&Tell
The Change My Son Brought, Seen Through Personal Data by Nathan Yau. We’re obviously big fans of Nathan and his work at Flowing Data. This great post illustrates a few of the insights Nathan gathered about how his life has changed since his son was born.

The Qualified Self: Going Beyond Quantification by Eric Boem and Jarrett Webb. No matter what adjective you prefer use to describe “the self” this article is a great example of what we see in show&tell talks at QS meetups around the world. The authors describe how they started to understand their sleep by combining many different data sets.

 

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What We Are Reading

Articles and Posts

Larry Page, TED, and Pooling our Medical Data by John Wilbanks. Health is a hard problem. A problem that people are using data, vast amounts of data, to help solve. This may work, but at the end of the day we have to remember that data is made of people, and those people deserve respect and privacy.

The Loneliness of the Sick Self-tracker by Jane Sarasohn-Kahn. Another great post about the current state of self-tracking and health data for the those trying to manage a chronic condition.

Patients + Providers + Technology = Engagement by Patti Brennan. In this post Patti describes her experience as director of the Project Health Design project funded by the Robert Wood Johnson Foundation and how self-tracking can power a new powerful form of observations of daily living.

Big Data Makes Invisible Air Pollution Visible by Intel Free Press. This short piece explains how community members in Portland, OR are collaborating with Intel Research to understand air pollution by deploying personal connected air sensing devices. Reminds me of the CitiSense project at the University of California, San Diego.

There’s No Such Thing as Gaining a Pound: Reconsidering the Bathroom Scale User Interface by Matthew Kay, Dan Morris, MC Shraefel, and Julie Kientz. Whether you’re using a scale, or hoping to design the next great one you owe it to yourself to read this excellent research paper. The research team examined how people actually us and think about their scales and provides a few design insights they believe could move the field forward.

The Year of the Quantified Self Revolution by Glenn Lubbert. A really wonderful piece a great member of our QS community. Glenn touches on conversations and experiences he’s had as he’s “gone down the rabbit hole” of self-tracking.

Data Scientists by Amelia Greenhall. Is our perception and use of the term “data scientist” a crack in the system? Is that a good thing? Amelia describes her experiences and what she’s thinking about this new class of employee.

You, Your Quantified Self, and all the (non) Quantified Others by Marco Van Hout. In this blog post Marco examines possible (present and future) scenarios for the self-tracking. His focus on how self-tracking and a data collection affects our communal relationships and societal norms is especially interesting.

In Defense of Google Flu Trends by Alexis Madrigal. If you’re like me you were saddened by the recent takedowns of the Google Flu Trend detection system. Data is supposed to help, right? In this article Alexis pushes past the naysayers as digs a bit deeper to find out why Flu Trends was built and how it was meant to be used. Hint – you still need people to help make sense of “big data.”

Making JSON as Simple as a Spreadsheet. I’ll be completely honest here. My programming skills end where JSON begins. Thankfully the Sunlight Foundation has developed a released a fantastic tool for people like me.

This Computer Can Tell When People Are Faking Pain by Greg Miller. First, a disclaimer. I used to work right next to the research group that developed this technology. Their research was always fun to learn about over quick coffee breaks or walks up the stairs in our building. Read this article with a bit of wonder and look for inspiration. If a computer with a camera can learn about pain and emotions how would you use it to learn about yourself?

Visualizations

Edward Tufte Wants You to See Better. This is a must read (or listen to) interview of Edward Tufte by Science Friday host, Flora Licthman.

I’m, at my best, on a kind of innocent and contrary posture, I think, wide-eyed, but somewhat skeptical posture.

My Personal Dashboard by Ahmet Al Balkan. I’m a big fan of self-made data dashboards. Especially when designers put them up on Githhub!

Everythign I Own by Thomas Stoller. This is just one in a series of self-tracking art projects by artist and student, Thomas Stoller. For this project Thomas took a photo of everything he owned and then resized the images to represent how much he actually uses them.

Vizual Statistix by Seth Kadish. This tumblr is an excellent source of inspirational visualizations.

Connected to the Self-Life and Re-Life by Luna Coppola. I’ve always been interested in how people use self-portraits as a form of self-tracking. This powerful photo project chronicles Luna’s experience with chronic kidney disease.

From the Forum

Raw heart rate data during sleep
Perpetual Life Hacker – Is it possible to hack Rock Climbing?
Dealing With People Privacy
Any Recommendations for Free Time Trackers

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What We Are Reading

Click, read, enjoy!

Articles and Posts

Meet the Teams Who are Building the World’s First Medical Tricorder by George Dvorksky. We’ve been following the Qualcomm Tricorder XPRIZE since it was announced. Now that only 10 teams remain it’s nice to get a feel for what some of the groups are working on. (Disclosure: Scanadu, one of the teams competing for the prize is a sponsor of QS. We are grateful for their support.)

How One Retailer’s Employees are Using Wearables by Andy Meek. Self-tracking technology is pushing into every corner of society. It’s no surprise that we’re seeing it being deployed in the the workplace. This is definitely something to keep an eye on and I look forward to more conversations about what it means to be “efficient and productive” at work.

The Great Discontent – Nicholas Felton by Ryan and Tina Essmaker. A great in-depth interview with designer, and personal data visualization specialist, Nicholas Felton.

I’m trying to lift the veil on the size, power, humanity, humor, and narrative potential of our data by making tools that allow people to leverage it.

What Your Activity Tracker Sees and Doesn’t See by Albert Sun and Alistair Dunt. If you’re wearing an activity tracker (Fitbit, Jawbone Up, Withings Pulse, etc.) this is a must read (and watch). The interactive elements do a great job of showing you how accelerometers work to translate movement data into information.

Me, My Quantified Self, and I by Kevin Nguyen. For some reason the release of the Reporter app has created a steady stream of philosophical explorations of what it means to track and understand “the self.” Add this to you reading list if you want to ask yourself, “Would David Hume use a Fitbit?”

Life through a camera by Carmen Pérez-Lanzac [SPANISH]. A fantastic exploration of the history and possible future of camera-based lifelogging.

Let’s get physical: Discovering data in the world around us by Anushka Patil. A nice post here recapping some of the work presented at the recent National Institute for Computer-Assisted Reporting conference. I especially enjoyed .

A DIY Artificial Pancreas System? Are we crazy? by Scott Leibrand & Dana Lewis. Some of the more technically minded people in the diabetes community are not waiting for the promised Artificial Pancreas Systems of the future and have set out to test and learn from a DIY solution. Absolutely amazing stuff here.

Data Analysis: The Hard Parts by Mikio L Braun. If you think machine learning is easy or the cure for your data analysis woes, think again.

Show & Tells

Generation ‘Y’ Can’t We Sleep by Scott Fetters. If you look beyond the title you’ll find a really nice example of someone practicing to try and find a way to get better sleep.

Visualization

An Introduction to D3 by Sam Selikoff. We’re huge fans of D3 here at QS Labs. This is a great place to start if you want to learn more about this powerful data visualization package.

From the Forum

Over Stimulation

Quantifying Relationships

Mapping your Location With Moves

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What We Are Reading

Another collection of thought-provoking items from around the web.

Articles & Posts

Plan to move from #quantified self to Qualified Self by Inga de Waard. Every now and then someone writes something that causes me to pump the brakes and really reflect on self-tracking and personal data collection. This is one of those time. Inga does a nice job here setting up her experience with self-tracking to understand her type 1 diabetes. She moves on to explore how “qualified data” might be a better source of information for personal growth, “I am more than my body, I am mind. So I want to understand more.”

The Bracelet of Neelie Kroes (in German) by Frank Schirrmacher. Can machines be trusted? Are we building and willingly wearing the handcuffs of the future by strapping tracking devices to our wrists? These questions are explored in this article. (If you’re like me you are probably wondering who Neelie Kroes is. Here’s some background info.)

Biggest Gene Sequence project to launch by Bradley J. Fikes and Gary Robbins. J. Craig Venter is at it again. Now that genome sequencing has passed the $1000 barrier he has set up a new company in order to recruit and sequence 40,000 people per year.

This Mediated Life by Christopher Butler. Another amazing piece of self-reflection spawned by the recently released Reporter App. Rather than reviewing the application, the author addresses what it means to self-track when we know we are our own observer. Do we bias our reflection and data submission when we know that each answer, each data point is being collected into a larger set? (This post reminded me of one of my favorite movie lines, “How am I not myself.” from I Heart Huckabees

The Open Collar Project. At a recent meeting I learned of this project to create an open-source dog tracking collar. Pet trackers are becoming more prevalent in the market, but the purpose of this project goes far beyond just understanding pet activity. I learned from the lead researcher, Kevin Lhoste, that they’re using this as a method to encourage and engage children in science and mathematics. Very neat stuff.

Twitch Crowdsourcing: Crowd Contributions in Short Bursts of Time [PDF] by Rajan Vaish, Keith Wyngarden, Jingshu Chen, Brandon Cheung, and Michael S. Bernstein. This research paper describes the results of a really interesting project to gather information from people using micro-transactions during the phone unlocking process. It appears that we can learn a lot from people in under 2 seconds.

The Open FDA. Not an article here, but I wanted to call attention to the new open initiative by the FDA. This new effort was spearheaded by Presidential Innovation Fellow, Sean Herron. If you’re interested in doing this type of work you can apply to be a fellow here.

Show&Tells (a selection of first person stories on self-tracking and personal data)

200 days of stats: My QS experience by Octavian Logigan. Octavian recounts the various data he’s collected including activity, sleep, email behavior, and work productivity. I really like how he clearly explains what tools he’s using.

A Year in Diabetes Data by Doug Kanter. We’ve featured Doug here on the blog before. From his amazing visualizations to his talks about his process, we’ve been consitently impressed and inspired by this work. In this post Doug recounts 2012 – “[...] the healthiest year of my life.” (Full disclosure: Doug sent me the poster version of his data and it is beautiful.)

Visualization

timkim_map
This visualization comes to us from Tim Kim, a design student based in Los Angeles.

The map shows different collections and documentations made during my cross country trip. Posts made during the trip on various social media sites are orientated and placed by the geological locations. The states are elongated by purely how I felt about the duration of going across the specific state. For example, driving through texas sucked (no offense). Different facts are layered and collaged across the map to create and express a collective, over-all image of the trip. Some quantifiable information, some quantitative information to create a psych-geolocal map.

Thumbs Up Viz A really nice website that highlights and explains the good pieces of data visualization popping up all over the web these days.

From the Forum

Tracking emotional experience
Test our a new app for sleep improvement
Measuring emotions through vital signs

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What We Are Reading

An extra long list for you to this time. Enjoy!

Articles & Posts

Beyond the Data Portal by Jed Sundwall. The open data refrain has been taken up by non-profits, local, and national governments around the world. Have we questioned what it really means to be good data stewards? A very nice post here that opens up a discussion about the role of data librarians to augment simple access with human-powered information wayfinding.

Could Behavioral Medicine Lead the Web Data Revolution? by John W. Ayers, Benjamin M. Althouse, and Mark Dredz. If you can look past the slightly antiquated use of the term “web data” here you’ll see a good critique of the current methods in behavioral health science and the role of personal data in medical and behavioral research.

Little data: Tracking your life through numbers by Dominic Smith. A nice short piece here on the art behind self-tracking,

Critics might ask why we should care about the aggregated, daily routine of a man most of us will never never meet. But fans would argue that these reports aren’t merely novelties for the coffee table—they represent data as art, a single year of human life parsed into graphs and charts.

Fitness Trackers Could Boost Kids’ Health, But Face Challenges, Experts Say by Tia Ghose. Activity trackers are all the rage these days, but can they be used to track and understand children’s physical activity?

Questioning the Quantified Self as it Marches Towards Mainstream by Matt Stempeck. A very thorough recap of a talk by Natasha Dow Shull given at the MIT Media Lab. It covers the history of self-tracking and the current trend towards algorithmic selfhood. Great read.

When quantified-self apps leave you with more questions than answers by Brendan O’Connor. The author takes at self-tracking and personal data through the lens of the newly released Reporter app. Reading this piece left me wondering, are questions the prominent artifact of a self-tracking practice?

Dan Hon’s Newsletter By Dan Hon. I know you get enough email already, but this is an exceptional project by Dan to express his ideas in the form of a daily newsletter. Covering the vast arena of techno-culture, it’s a great addition to my inbox. See his thoughts on Quantified Self in issue #15.

Why It’s OK to Let Apps Make You a Better Person by Evan Selinger. The ideas and considerations in this piece are as relevant today as they were when this article was published nearly two years ago.

Quantify Everything: A Dream of a Feminist Data Future by Amelia Abreu. A very interesting perspective on self-tracking and the Quantified Self movement by our friends at Model View Culture.

The Ethicist’s and the Lawyer’s New Clothes by I. Glenn Cohen [video]. An interesting lecture on the ethical issues surrounding the use and misuse of “smart clothing.”

Data Sharing Essay Competition by DNA Digest. A writing competition to explore themes around the positives and negatives of data sharing in the health research community.

Show&Tells (a selection of first person stories on self-tracking and personal data)

Quantify Yourself by Amo Utrankar. What happens when a medical student starts self-tracking so he can understand his future patients?

Between Week 1 and Week 4, my “compliance” fell from 96% to 63%. It takes a committed, conscious effort to record every meal, every vital sign, every exercise, every minute of the day. I hold a new-found respect for the diabetic patient who has to monitor his blood sugar, manage his appointments, and mind his meals; it’s a process that’s both distracting and exhausting.

I tracked every penny I spent for one year. Here’s what I learnt. by Todd Green. Ten lessons learned from a year-long meticulous tracking project.

I lost 1,000 hours of sleep in 1 year: My story as entrepreneur & new Dad by Nick De Mey. A father recounts his process of learning about his sleep, or lack thereof. (Editor’s note: Nick is a founding member of AddApp, a Friend of QS).

Visualizations

Screen Shot 2014-03-01 at 1.49.59 PMMy Facebook Messaging History by Person and Time. A great visualization and conversation with open source code so you can make your own.

 

 

 

 

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My Recent Exercise Log – Plotted. Another reddit user shares his exercise data from MyFitnessPal.

 

 

 

 

AekSBmnWhat can you learn from almost 3 years of Skype chat logs?. A simple, but nice word cloud visualization of chat logs.

In total there were 280114 words sent. Words that refer to oneself (such as: i, me, ich, my, mich, min, meiner, meine, meins, jag, mig, mir) were used 14995 times whereas words that refer to other people (like above list for others) were only used 6669 times! People in my Skype conversations like to talk about themselves… (which is mostly me. THERE, I did it again )

 

posegrid_ny_Selfiecity. An interesting exploration of new media visualization techniques and social media information processing by an outstanding group of researchers. Take a tour of the website then read Lev Monivich’s post about this new area of research and data visualization.

 

 

 

From the Forum

OPI Truesense for Sleep Tracking

Samsung Gear Fit

Tracking Pain/Discomfort – Thoughts?

Statistical Findings

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