Tag Archives: visualizations
We hope you enjoy this week’s What We’re Reading list!
The Wow of Wearables by Joseph Kvedar. An excellent post here in the wake of the “Smartphones vs. Wearables” hype in the past weeks. Favorite part:
“I’d have to say that reports of the death of wearables have been greatly exaggerated. The power of sensor-generated data in personal health and chronic illness management is simply too powerful to ignore.”
Survival of the Fittest: Health Care Accelerators Evolve Toward Specialization by Lisa Suennen. If you’re at all interested in the recent surge in health and healthcare focused accelerators this is for you. Excellent reporting. (Thanks for sharing Maarten!)
Your Brain Is Primed To Reach False Conclusions by Christie Aschwanden. Fascinating piece here about the nature of the “illusion of causality.”
A Few Throughs About Patient Health Data by Emil Chiauzzi. Emil, Research Director at PatientsLikeMe, lays out four point to consider when thinking about how to best use and grow self-collected patient data.
Having Parkinson’s since I was 13 has made me an expert in self-care by Sara Riggare.
I am the only person with the whole picture. To me, self-care is everything I do to stay as healthy as possible with a disease that is a difficult life companion. It entails everything from making sure I take my medication in the optimal way, to eating healthily, getting enough sleep, to making sure I stay physically active. I also make an effort to learn as much as I can about my condition; my neurologist says that I know more about Parkinson’s research than he does. I don’t find that odd, since he needs to try to stay on top of research in probably hundreds of neurological diseases, whereas I focus on just one.
From Bathroom to Healthroom: How Magical Technology will Revolutionize Human Health by Juhan Sonin. A beautifully written and illustrated essay on the design of our personal healthcare future.
Experimenting with sprints at the end of exercise routines by Gustavo M. Gustavo is a person with type 1 diabetes. After reading that post-exercise high intensity exertion might have an effect on blood glucose he put it to the test.
On Using RescueTime to Monitor Activity and Increase Productivity by Tamara Hala. Tamara walks us through the last three years of her RescueTime data and how she used that information to understand her work and productivity.
How Do You Find Time to Write? by Jamie Todd Rubin. Jamie has been writing for 576 consecutive days. How does he do it? A mixture of data and insight of course!
Say “I Love You” With Mapping by Daniel Rosner. Wonderful to see CHI papers ending up on Medium. This seems like a fun self-tracking/art project.
Cleaning up and visualizing my food log data with JMP 12 by Shannon Conners. Once again, Shannon displays a wonderful ability to wow us with her data analysis and visualization. Above is four years of food tracking data!
Two Trains: Sonification of Income Inequality on the NYC Subway by Brian Foo. Brian created this data-driven musical composition based on income data from neighborhoods the border the 2 train. Beautiful work.
Walgreens adds PatientsLikeMe data on medication side effects
How Open Data Can Reveal—And Correct—The Faults In Our Health System
Big Data is our Generation’s Civil Rights Issue, and We Don’t Know It.
Enjoy this week’s list!
Would You Share Private Data for the Good of City Planning? by Henry Grabar. The use of personal, and typically private, data for municipal planning and research is becoming more common. Strava, Uber, and other companies are passing along their user data to government bodies interested in understanding their constituents. In this article, past projects are described and new ideas are put forth about this growing trend.
The social network for people who want to upload their DNA to the Internet by Daniela Hernandez. A wonderful piece of journalism on the growing OpenSNP platform for open user-donated genetic data. Take some time and read the whole thing. (Full disclosure: My 23&Me data is available on OpenSNP.org.)
What Cognition-as-a-Service should mean? by Debidatta Dwibedi. The promise of fitness trackers for many is that the use of them will improve one’s fitness. Dwibedi expresses the desire for a tool to make one wiser by helping the user avoid logical fallacies. There are tools that can help, like spaced repetition.
Connected Car: Quantified Self becomes Quantified Car by Melanie Swan.
Sensors sensors everywhere
Near and far
On your wrist
In your home
And in your car.
What On Kawara’s Analog Wisdom at the Guggenheim Has to Offer a Digital World by Ben Davis. A fantastic peek into “On Kawara: Silence” a recently opened retrospective hosted at the Guggenheim.
He was making art about the “quantified self”—the contemporary self-improvement craze for tracking and charting one’s personal data—not just before the fitbit, but before the handheld calculator.
What My Hearing Aid Taught Me About the Future of Wearables by Ryan Budish. A great article here about how to think about possible ways our technology with change and shape the world around us. Special consideration is given to our ever evolving relationship with the tools of wearable computing.
I tried to quantify my sex life—and I am appalled (NSFW language) by Miles Klee. I went back and forth whether to include this here, but in the end I think it’s important to expose tracking of all types.
How I audited my daily media habits and improved the way I read by Lydia Laurenson. Lydia was concerned with the amount of bad content she was reading on the web.For a month, she rated the articles she read according to a 5-point scale with categories like “I’m actually angry I clicked this link” and “Wow, this is really cool or useful. I’m glad I saw this.” With these ratings, she was able to see which publications produced good contents, and which outlets gave her recommendations worth her time. You can check out her (empty) tracking spreadsheet here.
The Quantified Chef by Dan Brown. Dan doesn’t fancy himself a self-tracker, but was interested in understanding his cooking habits as the main dinner cook for his family. Some interesting finds and thoughts about what it means to collect data on yourself.
Using a Log Book and Excel To Assess Time Use by Morris Villarroel. Morris spoke about how he uses journals to track his life at our 2014 QS Europe Conference. In this post, he explains how he transfers hand-written data into Excel for more in-depth analysis.
Sid Lee Dashboard. Sid Lee, a creative agency, outfitted it’s Paris office with multiple sensors and data gathering systems powered by Arduinos to feed a beautiful real-time data dashboard. Make sure to click through for the interactive site and watch their short video.
Two Thousand And Fourteen by Tyler Baird. A sentence or two cannot do this amazing work justice. Click, read, and take in the 8,760 hours of Tyler’s tracked life.
The BMJ Today: Patient Centered Care
Health Data Exploration Project Announces Agile Research Project Awards
FDA makes official its hands-off approach to regulating health apps and medical software
Small thoughts on large cohorts
Selling your right of privacy at $5 a pop
Below you’ll find this week’s selection of interesting bits and pieces from around the web. Enjoy!
Open Books: The E-Reader Reads You by Rob Horning. A fantastic essay about the nature of delight and discovery, and how that may (is) changing due to data collected from e-readers. For those interested in books and data this article By Buzzfeed’s Joseph Bernstein is also an interesting read.
Flashing lights in the quantified self-city-nation by Matthew W. Wilson. Quantified Self, smart cities, and Kanye West quotes – this commentary in the Regional Studies, Regional Science journal has it all. Read closely, especially the final paragraph, which gives space to think about the role the institutions and companies that provide cities with the means to “be smart” have in our in social and urban spaces.
Most Wearable Technology Has Been a Commercial Failure, Says Historian by Madeleine Monson-Rosen. This is a interesting book review for Susan Elizabeth Ryan’s Garments of Paradise which had me thinking about the nature of wearables, customization, and expression.
‘The Cloud’ and Other Dangerous Metaphors by Tim Hwang and Karen Levy. This was mentioned so many times over the last few days by so many smart friends and colleagues that I had to set aside time to read it. It was time well spent. The authors make the case that how we talk about data (personal, public, mechanical, and bioligical) is tied to the metaphors we use, and how those metaphors can either help or hinder the broader ethical and cultural questions we find ourselves grappling with.
Why the Internet Should Be a Public Resource by Philip N. Howard. This isn’t the first, nor will it be the last, argument for changing the way we think about and regulate the Internet. Worth reading the whole things, but in case you don’t consider this point:
And then we might even imagine an internet of things as a public resource that donates data flows, processing time, and bandwidth to non-profits, churches, civic groups, public health experts, academics, and communities in need.
Computers Are Learning How To Treat Illnesses By Playing Poker And Atari by Oliver Roeder. How does research into algorithms and AI intended for winning poker games morph into something that can optimize insulin treatment? An interesting exploration on the background and future implications of computers that can learn how to play games.
Data Stories #45 With Nicholas Felton. by Enrico Bertini and Moritz Stefaner. In this episode of the great Data Stories podcast Nicholas Felton talks about his background, his interest in typography, and what led him to start producing personal annual reports. Super fun to listen to them geek out about the tools Nicholas uses to track himself.
Increasingly, people are tracking their every move by Mark Mann. A great peak into some of our QS Toronto community members and how they use self-tracking.
Quantified Existentialism by Ernesto Ramirez. I’m putting this last here because it feels a bit self-congratulatory. Earlier this week I took some time to examine how common it is for people to express their relationship with what counts when they use self-tracking tools. It was a fun exercise.
Insights From User Generated Heart Rate Variability Data by Marco Altini. While not a personal show&tell (however, I’m sure his data is in there somewhere), this great post details what Marco was able to learn about HRV based on 230 users and 13,758 recordings of HRV.
Quantify This Thursday: No Coding Required by Kerri MacKay. A bit different post here, more of a how-to, but I found it really compelling the lengths Kerri went to get get her Fitbit data to show up on he Pebble watch. I was especially drawn to her explanation of why this method is important to her:
The reality is, getting nudges every time I look at the clock or dismiss a text notification on my Pebble (via my step count) is yet another way to make the wearing-a-wearable less passive and the data meaningful.
Correlating Weight with Blood Pressure by Sam. A short and simple post detailing how Sam used Zenobase and his iHealth devices to see how weight loss was associated with his blood pressure.
The Effect of End of Year Festivities on Health Habits by Withings. The above is just one of four great visualizations from Withings exploring how the holidays affect how users sleep, move, and weight themselves. Unsurprisingly people are less likely to weight themselves on Christmas day (I looked at my data, I am among those non-weighers).
Simon Buechi: In Pure Data by Simon Buechi. A simple, elegant dashboard intended to represent himself to the world.
Grad School Coding Analysis by Matt Yancey. The above is just a preview of two fantastic visualizations that summarize the coding Matt did while enrolled in the Northewestern Masters of Analytics program.
News Year’s Eve Celebration in Steps by Lenna K./Fitbit. A fun visualization describing differences in how people in different age groups moved while celebrating the new year.
From The Forum
How do I visualize information quickly? (mobile app)
Monitoring Daily Emotions
Best Heartrate Monitor that syncs with Withings Ecosystem
Is the BodyMedia Fit still alive?
Capture Online Activities (and More) into Day One Journal Software (Mac/iOS)
We hope you enjoy this week’s list!
The Global Open Data Index by The Open Knowledge Foundation. This isn’t an article, but rather an really nice portal to explore open data sets from around the world.
Eight things we learned about HealthKit from Duke, Oschner by Jonah Comstock. An interesting piece here detailing how two large healthcare systems are using Apple’s Healthkit.
Connected Health: Improving Patients’ Engagement and Activation for Cancer-Related Health Outcomes by the President’s Cancer Panel. Very short publication here that outlines how the President’s Cancer Panel is thinking about new changes in the health system and health technology.
Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images by Anh Nguyen, Jason Yosinksi, and Jeff Clune. This in not a typical entry into our weekly What We’re Reading as it doesn’t appear to be directly related to self-tracking or Quantified Self. However, I found it fascinating and a great reminder that algorithms are not infallible.
Visualizing HR, HRV, and GSR While Watching ‘Interstellar’ by Bob Troia. Inspired by a Reddit user who tracked his HR while viewing Interstellar, Bob Troia set out explore his full physiological response by tracking heart rate, heart rate variability, and galvanic skin response. Some great data in here!
Stress Snail by Pavel Zakharov. Pavel uploaded this unique visualization to our QS Forum earlier this week. This visualization represents his heart rate, activity, and stress during a particularly stressful day when he was completing a driving test. If you have ideas or thoughts on the visualization make sure to share them in our forum!
This Week on QuantifiedSelf.com
Greg Schwartz: Quantified Dating
David Joerg: Building My Personal Operating System
LifeLogging: Personal Big Data by Cathal Gurrin, Alan Smeaton, and Aiden Doherty. A wonderful overview of the field of lifelogging. Special attention is given to how information retrieval plays a role in how we can understand and use our lifelogs.
What happens when patients know more than their doctors? Experiences of health interactions after diabetes patient education: a qualitative patient-led study by Rosamund Snow, Charlottle Humphrey, and Jane Sandall. In this qualitative study, the authors engaged with 21 patients with type 1 diabetes who had developed expertise about their condition. Some interesting findings about how healthcare providers may be uncomfortable with patient who understand themselves and their condition. (Thanks to Sara Riggare for sharing this article with us!)
Internet of You: Users Become Part of the City-as-a-System by Tracy Huddleson. An good look into how wearables and personal technology might have an impact on the public infrastructure, institutions, and spaces.
Welcome to Dataland by Ian Bogost. Not sure how I missed this one piece from late July, but glad I stumbled across it this week. Ian Bogost takes a tour through the actual and imagine implications of the Disney Magic Band. I especially enjoyed the historical context describing the history of futurism at Disney.
Gary Wolf on Cool Tools Show #15. QS co-founder, Gary Wolf, speaks with Mark Frauenfelder and Kevin Kelly on the Cool Tools Podcast about his favorite self-tracking tools and what he’s learned from using them.
My heart rate during Interstellar (via Basis Peak) by Reddit user javaski. An nice use of the BasisRetreiver tool to download and analyze heart rate data from the new Basis Peak device.
Activity Time vs. Device Wear Time by Shannon Conners. Shannon plotted her actual wear time using the BodyMedia Fit against the activity data to show that low activity numbers are probably caused by hotter summer months when wearing the armband caused unwanted tan lines.
“If I had not explored my activity and usage data first to remind me of this usage pattern, I could have created any number of plausible explanations for why my activity levels were so much lower during the hot North Carolina summer months.”
We hope you enjoy this week’s list of articles, posts, show&tell descriptions, and visualizations!
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.”
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.
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.“
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.
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.
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!
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.
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.
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.
It’s About Time by Hunter Whitney. A nice post here about the different methods of visualizing temporal data.
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)
We hope you enjoy this week’s list!
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.
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!
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!
Tracking Energy use at home by reddit user mackstann.
“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).”
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!
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.
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.
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.
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.
What Time of Day Do People Run by Data @ Runkeeper. As a runner I can’t get enough of these visualizations and data analyses.