Topic Archives: What We’re Reading

What We Are Reading

We’ve assembled another great list of articles, posts, and other interesting ideas for you to enjoy.

Articles
Billy Beane’s Ascendant A’s Are Playing a Brand-New Brand of Moneyball by Will Leitch. I know what you’re thinking, “What’s an article about baseball doing in this list?” First, it’s about how the Oakland Athletics are using metrics to improve their team. And two, I was struck by the following:

“Instead, Beane and his front office have bought in bulk: They’ve brought in as many guys as possible and seen who performed. They weren’t looking for something that no one else saw: They amassed bodies, pitted them against one another, were open to anything, and just looked to see who emerged. Roger Ebert once wrote that the muse visits during the act of creation, rather than before. The A’s have made it a philosophy to just try out as many people as possible—cheap, interchangeable ones—and pluck out the best.”

Sounds a lot like our old friend, Seth Roberts, describing the value of self-experimentation - start small, do a lot of them, learn by doing.

Build Great Models . . . Throw Them Away by Mark Ravina. A digital humanities researcher makes the case for using data and statistical methods of modeling not to answer questions, but to come up with better questions. Really enjoyed the great examples in this post.

App data reveals locations, times and distances of Calgary’s runners and cyclists by Meghan Jessiman. A collaboration between RunKeeper and the local Calgary Herald newspaper led to some interesting findings and, of course, some activity heat maps.

A Digital Dose of Magic Medicine by Naveen Rao. Naveen connects the dots between the recent controversy surrounding Doctor Oz to the possibly misplaced hopes we’re putting in tools like HealthKit.

9-Volt Nirvana by RadioLab. This episode of the always interesting RadioLab tells the story of a journalist who was hooked up to a tDCS device for a sniper shooting exercise. The device helped her accuracy in the simulation, but then there was an unexpected after-effect. For three days afterward, the voices of self-doubt and self-abnegation receded from her consciousness. She talks about that experience directly on her blog. (Thanks to Steven Jonas for sending this one in!)

Tracking Sleep With Your Phone by Belle Beth Cooper. A great roundup here of iOS and Android apps you can use to track sleep. I especially appreciated the nice discussion of the current limitations of using mobile apps to track and understand sleep.

From Missiles To The Pitch: The Story Behind World Cup Tech by Melissa Block and NPR. If you’re wondering how FIFA is able to track the movement of individuals players during this year’s World Cup then this is for you. You can also check out all the data on FIFA’s website here.

Show&Tell
Productivity, the Quantified Self and Getting an Office by Bob Tabor. Bob works at home and was curious about how productive he really was. After using RescueTime he realized maybe he wasn’t getting the productive time he really need.

Basis to Roambi by Florian Lissot. Florian wanted to explore his Basis data. After using Bob Troia’s great data access script and some additional tools to aggregate multiple files he was able to create some great visualizations with Roambi and learn a bit more about his daily patterns of activity.

Do you have a self-tracking story you want to share? Submit it now!

Visualizations
losangeles-transport
How We Move in Cities by Human.co. It seems that making heatmaps based on movement is all the rage these days. Human has gone one step further than previous entries in this category by including motorized travel alongside cycling, walking, and running data. Don’t forget to check out the amazing GIFs as well.

cecinestunedataviz
This is Not a Data Visualization by Michael Thompson.

“[...] visualizations are not the data. The data is not the sum of the experience. We’ve been inappropriately using data visualizations as the basis for statements and conclusions. We’re leaving out rigorous statistical analysis, and appropriate qualifiers such as confidence intervals. It’s exciting that we’ve become more and more a society of pattern-seekers. But it’s important that we don’t become lazy and cavalier with what we do with those observations.”

MSFTdataviz
Reflections on How Designers Design With Data [PDF] by Alex Bigelow, Steven Drucker, Danyel Fisher, and Miriah Meyer. Researchers from Microsoft and the University of Utah sought out to understand how designers go the process of understanding data and creating unique visualizations.

Do you have a QS data visualization you want to share? Submit it now!

From the Forum
Best passive GPS Logger?
Quantified Baby
Android App for Self Surveys

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What We Are Reading

We’ve compiled another list of interesting personal data and Quantified Self articles, self-tracking stories, and data visualizations. Enjoy!

Articles

Experimental evidence of massive-scale emotional contagion through social networks by Adam Kramer, Jamie Guillory, and Jeffrey Hancock. Facebook engaged in a large study to see if emotional states could be transferred/changed via the emotional content of the News Feed. A lot of hubbub recently about this research article related to what it means to knowingly consent to research.

Who Owns Your Personal Data: The Incorporated Woman. Jennifer Morone has added herself to a long list of individuals making a statement against the commercialization of personal data. What started as a design assignment has morphed into a statement against others profiting and controlling personal data. (Immediately remind me of this Kickstarter project.)

Quantified Self and the Ethics of Personal Data by Ian Forrester. Ian does a great job here of exploring current conversations about the variety of ethical questions that come with creating, using, and owning personal data.

Visualizing Algorithms by Mike Bostock. Mike is the creator and steward of the d3.js data visualization library. In this fascinating post, he recounts one of his recent talks about how visualization can be used to understand how algorithms work.

“[...] algorithms are also a reminder that visualization is more than a tool for finding patterns in data. Visualization leverages the human visual system to augment human intellect: we can use it to better understand these important abstract processes, and perhaps other things, too.”

Biometric Shirt for Astronauts Gets Antarctic Tryout by Eliza Strickland. Eliza describes a “try-out” for using self-tracking technology to better understand vital signs and activity during space travel.

Show&Tell

My Solution for Quantified Self: Prompted Data Aggregation by Jonathan Cutrell. Jonathan decided to build his own simple system for self-directed data collection prompts. “While they may be simple data points, and while the questions will repeat, the concept is simple: my computer asks me a question, and tracks my answer for me.”

Quantified Splunk: Tracking My Vital Signs by David Greenwood. David describes how he uses Splunk, a data monitoring and analysis tool, to help him track and make sense of new personal health data he’s collecting. It will be interesting to see what he learns as he starts adding and exploring more of his self-tracking data.

How I Wrote 400K Words in a Year by Jaime Todd Rubin. In March of 2013, Jaime decided he was going to try and write every day. In this post he describes some of the lessons he learned through tracking his writing practice. I was particularly drawn to his methods for tracking all his writing through Google Docs.

Do you have a self-tracking story you want to share? Submit it now!

Visualizations

Withings-via-IFTTTCharting Withings Data Using IFTTT, Google Spreadsheets, and d3.js by Dan Harrington. Dan didn’t like the way Withings presented weight data in it’s visualization. So, he put together a tutorial to show how you can grab your Withings data via IFTTT, import it into a Google Spreadsheet, then visualize it using d3.js, an open-source data visualization library.

 

 

MapRunKeeper1.5 Million Walks, Runs, and Bike Rides by Mapbox and RunKeeper. The Mapbox team worked with Runkeeper to map publicly shared routes. Really interesting to zoom around the world map to see where people who use RunKeeper are exercising.

 

 

Do you have a QS data visualization you want to share? Submit it now!

From the Forum

HealthKit
Lifelogging via Calendar Application
Help Analyzing Text Files?
Breakout: Productivity Tracking

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What We Are Reading

Enjoy this week’s list of articles, show&tells, and visualizations!

Articles
Strava is Just the Start: The Promise of Open Trail Data. by Mary O’Connor. Data standards might be one of the most boring topics that has a real impact on our daily interactions with data. In this short piece you’ll learn how public transit data standards that help you know when the bus or subway is arriving are influencing a new standard for public trail mapping.

A Stroke Diagnosed With a Selfie by Olga Khazan. A brief piece here tells the story of Stacey Yepes, a woman who used her phone to record the onset of her second stroke.

On Behavior Modification and Agency by Rebecca Pardo. Do our devices change our actions or do we? This nice post by Dr. Pardo is a recommend read for anyone thinking about behavior change in the context of Quantified Self apps and tools.

Making Art out of Everyday Life by Aimme Levitt. If you’re in or around Chicago this summer I highly suggest visiting the Elmhurst Art Museum for the “Lifeloggers: Chronicling the Everyday” exhibit. If you can’t make it, this article about the exhibit will have to suffice.

Visualization of Human Behavior Data: The Quantified Self [pdf] by Alessandro Marcengo and Amon Rapp. This book chapter outlines ideas and insights about self-tracking from a research standpoint. The two authors go on to also describe new methods of visualization and data management they believe could positively impact people using self-tracking tools now and in the future.

Show&Tell
The DIY Pancreas by Scott Leibrand and Dana Lewis. This isn’t a single post, but rather a long story about two people working together to use data to help learn about and take control of type 1 diabetes. You can start here to learn why it was necessary to hack a system together in the first place.

Can Heart Rate Variability be Useful in Predicting A CF Exacerbation? bib Julie Desch. This is a pretty early account of what Julie is learning by measuring her HRV, but it will be interesting to follow her story along the way!

Visualizations
visitsVisits. Visits isn’t just a neat visualization. It’s a online platform to explore your location history, trips, and what you’ve done along the way. Currently it works with OpenPaths and Google Location history data as well as geotagged Flickr photos.

 

 

 

keystrokes

My Working Pulse by Victor Pascual. Victor uses an open-source keylogger to track his computer usage and work habits. This visualization, made with Tableau, shows his keystrokes by day and per month.

 

 

 

vizcat

Data Visualization Catalogue by Severino Ribecca. If you’re interested in the many different methods of data visualization, this is a good place to start. Severino has created a nice directory here that explains many of the different common visualization methods and the tools you can use to create them. To learn more about this project you can watch his talk at the London QS meetup here.

 

 

 

From the Forum
Zeo Sleep Monitor – Data Viewer Application

Home Potassium Testing

Jawbone Up – How to Access Intra-day Data

Saga vs. Moves

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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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