Tag Archives: visualizations

What We Are Reading

We hope you enjoy this week’s list of articles, posts, show&tell descriptions, and visualizations!

Articles
I’m Terrified of My New TV: Why I’m Scared to Turn This Thing On — And You’d Be, Too by Michael Price. Michael, a lawyer at the Brennan Center for Justice at the NYU School of Law, describes his experiences with his new “smart” TV. More sensors means more records being stored somewhere you might not have access to. Especially interesting when your device picks up every word you say:

“But the service comes with a rather ominous warning: ‘Please be aware that if your spoken words include personal or other sensitive information, that information will be among the data captured and transmitted to a third party.’ Got that? Don’t say personal or sensitive stuff in front of the TV.”

Public Perceptions of Privacy and Security in the Post-Snowden Era by Mary Madden. A great report from the Pew Research Internet Project. I don’t want to give away any of the juicy stats so head over and read the executive summary.

This Is What Happens When Scientists Go Surfing by Nate Hoppes. It’s not all privacy talk this week. This is a fun article exploring how new sensors and systems are being used to monitor surfers as they train and practice.

How Private Data is Helping Cities Build Better Bike Routes by Shaun Courtney. We covered the new wave of personal data systems and tools feeding data back into public institutions a bit before. Interesting to hear that more cities are investing in understanding their citizens through the data they’re already collecting.

What Do Metrics Want? How Quantification Prescribes Social Interaction on Facebook by Benjamin Grosser. Ben is most commonly known around the QS community as the man behind the Facebook Demetricator, a tool to strip numbers from the Facebook user interface. In this article, published in Computational Culture, he lays out an interesting argument for how Facebook has created a system in which the users, “reimagine both self and friendship in quantitative terms, and situates them within a graphopticon, a self-induced audit of metricated social performance where the many watch the metrics of the many.”

Show&Tell
The Cubicle Gym by Gregory Ferenstein. Gregory was overweight, overworked, and in pain. He started a series of experiments to improve his help, productivity, and wellbeing. I enjoyed his mention of using the Quantified Mind website to track cognition. If you find his experience interesting make sure to read a previous piece where he explains what happened when he replaced coffee with exercise.

Maximizing Sleep with Plotly and Sleep Cycle by Instructables user make_it_or_leave_it. A really nice step by step process and example here of graphing an making sense of Sleep Cycle data.

ToiletMatters Toilet Matters by Chris Speed. A super interesting post on what a family was able to learn by having access to data on of all things, the amount of toilet paper left on a roll and when it was being used. Don’t forget to read all the way to end so you can get to gems like this:

“[…]the important note is that the source of this data is not only personal to me, it is also owned by me. We built the toilet roll holder and I own the data. There are very few products or smart phone apps that I can say the same about. Usually I find myself agreeing to all manner of data agreements in order to get the ‘free’ software that is on offer. The toilet roll holder is then my first experience of producing data that I own and that I have the potential to begin to trade with.“

Visualizations
e-traces-lesia-trubat-01_800 E-Traces by Lesia Trubat. A beautiful and fun project by recently graduated design student, Lesia Trubat. Using adruinos and sensors places on the shoes of dances she was able to create unique visualizations of dance movement. Be sure to watch the video here.

 

jepricer Animated Abstractions of Human Data by James E. Pricer. James is an artist working on exposing self-collected data in new and interesting ways. Click through to see a dozen videos based on different types of data. The image above is a capture from a video based on genotypes derived from a 23anMe dataset.

The Great Wave of Kanagawa by Manuel Lima. Although this is an essay I’m placing it here in the visualization section because of it’s importance for those working on the design and delivery of data visualizations. Manuel uses the Great Wave off Kanagawa as a wonderful metaphor for designing how we visually experience data.

D3 Deconstructor by UC Berkeley VisLab. A really neat tool here for extracting and repurposing the data powering at D3.js based visualization.

From the Forum
myStress
Diagnosed sleep apnea. Looking for metrics pre/post treatment
Trend Research
New Self Quantifier
Memosee

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What We Are Reading

We’ve put together an nice list of articles for you to enjoy this weekend. As always, please get in touch if you have something you’d like us to share!

Articles
Finding Patterns in Personal Data by Kitty Ireland. Another great post from Kitty about using personal data to uncover interesting, and sometimes surprising, patterns. Some great examples in this post!

The Tale of a Fitness-Tracking Addict’s Struggles With Strava by Jeff Foss. Just because you can track, and you can get something out of it, might not mean you should. (I had a similar experience on a recent trip to Yosemite so this article was quite timely.)

Algorithmic skin: health-tracking technologies, personal analytics and the biopedagogies of digitized health and physical education by Ben Williamson. Quantified Self and self-tracking tools are not limited to only being used by conscious and willing adults. They’re also being developed for and used by a growing number of children and adolescents. What does this mean of health and fitness education, and how should we think about algorithms in the classroom and gym?

Seeing Ourselves Through Technology: How We Use Selfies, Blogs and Wearable Devices to See and Shape Ourselves by Jill Walker Rettberg. I just started this book and it appears offer some interesting perspectives on the current cultural shift toward technically mediated representation. The book includes a chapter on Quantified Self and is available for download in PDF and EPUB under a CC BY license.

Show&Tell
Why Log Your Food by Amit Jakhu. Amit started tracking his food in March (2014) and has since learned a few things about his preconceived notions about his diet, food, and what it takes to keep track of it all.

Even When I’m active, I’m sedentary by Gary Wolf. Gary and I used our recently released QS Access app to download his historical step data. Using some simple charting in Excel we found some interesting patterns related to his daily movement.

Visualizations
SleepJewel
When Do I Sleep Best by Jewel Loree. Jewel presented her sleep tracking project at a recent Seattle QS Meetup. The image above is just a small piece of a great set of visualizations of her data gathered with SleepCycle and Reporter apps.

20min
Lightbeam Visualization by Simone Roth. Interesting tool described here to track how your data and web activity is being tracked. You can check out the Firefox extension here.

Minard It’s About Time by Hunter Whitney. A nice post here about the different methods of visualizing temporal data.

Respiration Machine 0.3 (bellows) by Willem Besselink. A neat physical visualization and art project that represents breath using a Hoberman sphere.

From the Forum

There has been a lot of great discussion on the forum lately. Check out some of the newest and most interesting topics below.

QS Access App
Hypoxic – An App for Breathing Exercises with HRV Tracking
Sleep Tracking & Hacking Google Hangout
Personal Analytics Service for Software Developers
Using Facial Images to Determine BMI
The Right Tool? (tracking and plotting sleep)

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What We Are Reading

We hope you enjoy this week’s list!

Articles
Big Data in the 1800s in surgical science: A social history of early large data set development in urologic surgery in Paris and Glasgow by Dennis J Mazur. An amazing and profoundly interesting research paper tracing the use of “large numbers” in medical science. Who knew that is all began with bladder stones!

Civil Rights, Big Data, and our Algorithmic Future by Aaron Rieke, David Robinson and Harlan Yu. A very thorough and thoughtful report on the role of data in civil and social rights issues. The report focuses on four areas: Financial Inclusion, Jobs, Criminal Justice, and Government Data Collection and Use.

Caution in the Age of the Quantified Self by J. Travis Smith. If you’ve been following the story of self-tracking, data privacy, and data sharing this article won’t be all that surprising. Still, I can’t help but read with fascination the reiteration of tracking fears, primarily a fear of higher insurance premiums.

Patient Access And Control: The Future Of Chronic Disease Management? by Dr. Kaveh Safavi. This article is focused on providing and improving access and control of medical records for patients, but it’s only a small mental leap to take the arguments here and apply them all our personal data. (Editors note: If you haven’t already, we invite you to take some time and read our report: Access Matters.)

Perspectives of Patients with Type 1 or Insulin-Treated Type 2 Diabetes on Self-Monitoring of Blood Glucose: A Qualitative Study by Johanna Hortensius, Marijke Kars, and Willem Wierenga, et al. Whether or not you have experience with diabetes you should spend some time reading about first hand experiences with self-monitoring. Enlightening and powerful insights within.

Show&Tell
Building a Sleep Tracker for Your Dog Using Tessel and Twilio by Ricky Robinett. Okay, maybe not strictly a show&tell here, but this was too fun not to share. Please, if you try this report back to us!

Digging Into my Diet and Fitness Data with JMP by Shannon Conners, PhD. Shannon is a software development manager at JMP, a statical software company. In this post she describes her struggle with her weight and her experience with using a BodyMedia Fit to track her activity and diet for four years. Make sure to take some time to check out her amazing poster linked below!

Visualizations
The following two visualizations are part of Shannon Conners’ excellent poster detailing her analysis of data derived from almost four years of tracking (December 2010 through July 2014). The poster is just excellent and these two visualizations do not do it justice. Take some time to explore it in detail!

SC_calorieweight

SC_sleep

Tracking Energy use at home by reddit user mackstann.

EnergyApp

“The colors on the calendar represent the weather, and the circles represent how much power was used that day. The three upper charts are real-time power usage charts, over three different time spans. I use a Raspberry Pi and an infrared sensor that is taped onto my electric meter. The code is on github but it’s not quite up to date (I work on it in bits and pieces as time permits I have kids).”

From the Forum
Help With Livestrong Data Export
Need Help Deciding Which Device
New to Fitness Tracking

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What We Are Reading

Before we get to this week’s list we want to make sure you know about our recent conference announcement. This week we announced our QS15 Conference & Exposition. This will be our seventh conference and is sure to be an amazing event. We invite you to register today!

Now on with the good stuff!

Articles
Why Big Data Won’t Cure Us by Gina Neff. A great research paper in the aptly name journal, Big Data. Dr. Neff specifically focuses on the perils of assuming “all the data” will solve the numerous health healthcare problems and then lays out five elements to consider as data, big and small, becomes part of our healthcare experience.

More Than Meets the Eye: NASA Scientists Listen to Data by Kasha Patel. Apparently the scientists studying the sun have so much data to sift through that listening to signals is a valuable alternative to visualizing it. (via our friend Joost Plattel)

Quantified Dating, Relationships, and Sex by Kitty Ireland. A great series of three posts by Kitty that explores a variety of examples of using self-tracking in the most intimate of situations – dating, long-term relationships, and sex.

A Look Back At the Evolution of Wearable Tech. In the wake of the recent Apple Watch announcement I love being able to look back at the history of different how technology has made inroads into our lives.

Show&Tell
The Baby Measureur by Erich Morisse. Erich is a proud father of a new child and like any new dad with data skills he started tracking some important metrics such as feeding time, feeding duration, and of course diaper changing!

A Day at Burning Man, Visualized Through Health Tracker Data by Gregory Ferenstein. Gregory takes his Basis Band to Burning Man and shows us what he learned.

Visualizations
scotto-prism
My Most Intimate Self Portrait by Scott Ogle. Scott has a wonderful post here about a visualization of his almost 30,000 text messages.

If I look closely, I can see a new job, vacations and a death in the data. I can even see where I moved past it all and stopped feeling the need to communicate so much. It may just be text messages, but it all correlates to things that are really real.

And all of it is captured in this graph.

AmsterdamMap
9 Days in Amsterdam – Tracking my Mobility in Bicycle Wonderland by Patrick Stotz. Patrick traveled to Amsterdam and tracked his stay using OpenPaths. I especially enjoyed how he was able to segment his means of transportation. If you’re interested in maps I suggest take a look at his great checklist for making geodata visualizations and this list of geodata tools.

RunkeeperTime
What Time of Day Do People Run by Data @ Runkeeper. As a runner I can’t get enough of these visualizations and data analyses.

From the Forum
How to Replicate SleepCycle?
What Application Can Monitor My Levels of Energy?
HealthKit
Quantified Baby

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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

Want to receive the weekly What We Are Reading posts in your inbox? We’ve set up a simple newsletter just for you. Click here to subscribe.  Do you have a self-tracking story, visualization, or interesting link you want to share? Submit it now!

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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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Stefan Hoevenaar: My Father, A Quantified Diabetic

Stefan Hoevenaar’s father had Type 1 Diabetes. As a chemist, he was already quite meticulous about using data and those habits informed how he tracked and made sense of his blood sugar and insulin data. In this talk, presented at the 2014 Quantified Self Europe Conference, Stefan describes how his father kept notes and hand-drawn graphs in order to understand himself and his disease.

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What We Are Reading

Enjoy this week’s reading list. If you’d like to submit something for future What We’re Reading posts we invite you to get in touch!

Articles
Data Journalism Needs to Up Its Own Standards by Alberto Cairo. The influx of new data-based journalistic endeavors seems to grow by the day. In this great piece Alberto Cairo presents four suggestions for those practicing that art and science of data-based reporting.

Big Data Should Not be a Faith-Based Initiative by Cory Doctorow. The idea of “big data” as a miraculous fountain of new knowledge is widespread. In this article Cory Doctorow brings to light some of the major concerns about personal data and the true possibility of de-identification.

Data Privacy, Machine Learning, and the Destruction of Mysterious Humanity by John Foreman. This is a long read, but definitely worth the time. If you’re like me you’ll spend the next few hours (day?) thinking about yourself, the various companies and organizations consuming your data, and how your life may (or may not) be shaped by the information you willingly hand over.

Privacy Behaviors of Lifeloggers using Wearable Cameras [PDF] by Roberto Hoyle, Robert Templeman, Steven Armes et al. This research paper paper offers a good glimpse into the the concerns and real behaviors of people using photo lifelogging systems. This is an area we’ve previously explored (see Kitty Ireland’s great write-up about our lifelogging town hall at QSEU13) and we expect to continue discussing.

Show&Tell
Battery Life, 6mo Checkup By James Davenport. It may seem odd to have a post about tracking battery life from a laptop here in the Show&Tell section, but this is a really neat post. As part of tracking his laptop battery he also tracked his usage and led to some interesting data about his sleep. (Don’t forget to check out the post that kicked off his battery tracking.)

Bringing My Data Together by John T. Moore. John is on a journey of improving his health and being more active through self-tracking/monitoring. In this post he pulls together some of his most important data, but I also suggest reading his summary of how he got started with self-tracking.

Visualizations

carsharing
Seven Days of Carsharing by Density Design. Not exactly personal data here, but some beautiful visualizations based on one week of data from the Enjoy, a carsharing service in Milan.

aprilzero
Aprilzero by Anand Sharma. I stumbled on this website recently via the #quantifiedself feed on Twitter. The visualizations and interactivity on this personal data site are really nice.

LR_annualreports
Lee Rogers’ Annual Reports by Lee Rogers. Lee has been tracking different aspects of his life for more than three years. Since 2011 he’s put together Annual Reports detailing his personal data. You can view his 2011, 2012, and 2013 reports on his website.

From the Forum
Devising Experiments
Looking for a General QS Device
Masters Thesis: Self-Tracking Motivations
Greetings From Germany

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Jamie Aspinall on Learning From Location Data

Jamie Aspinall was interested in what his location history could tell him. As a Google Location user, his smartphone is constantly pinging his GPS and sending that data back to his Google profile. Using Google Takeout Jamie was able to download the last four years of his location history, which represented about 600,000 data points. In this talk, presented at the London QS meetup group, Jamie describes his process of using a variety of visualizations and analysis techniques to learn about where he goes, what causes differences in his commute times, and other interesting patterns hidden in location data.

You can also view his presentation here.

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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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