Tag Archives: data
A long list for this week’s What We’re Reading. I actually had to stop myself from adding in even more visualizations and show&tell examples! We’re always on the lookout for more though, so make sure tweet us your favorite links!
Fitted by Moira Weigel. A very thoughtful essay on gender, identity, and confession – all while using the Fitbit as the narrative backdrop.
What kind of love does the FitBit prepare us to feel? Is it self-love? Or is even the self of the exorexic a kind of body armor?
How to Build a Smart Home Sensor by Dave Prochnow. If you have 2 hours, $95, and know how to solder, then you too can build this DIY sensor to measure the temperature, humidity, light, and noise for any room in your home. If someone builds and tests this please let me know (Would love to see air quality sensors included too!)
It’s Hard to Count Calories, Even for Researchers by Margot Sanger-Katz. New research shows Americans are eating less, but can we really trust the data? Margot does an excellent job here of rounding up the various ways we measure food consumption in the United States while coming to a commonly heard conclusion – food tracking is just plain hard.
Hadley Wickham, the Man Who Revolutionized R by Dan Kopf. If you’re knee deep in data analysis, or just like poking around in stats software, you’ve probably heard of and used R. And if you’ve used R, then there is a good chance you’ve used many of the packages written by Hadley Wickham. Great read, if for nothing else you learn what the “gg” in ggplot2 stands for.
Heart patient: Apple Watch got me in and out of hospital fast by Neil Versel. When Ken Robson wasn’t feeling well he turned to his Apple Watch. After noticing lower than normal heart rate readings his checked himself into the emergency room and soon found out his hunch was right, he had sick sinus syndrome.
New Australian experiment rewards joggers with 3D printed chocolate treats based on exercise data by Simon Cosimo. Sign me up!
How Does Giving Blood Affect Your Iron Levels? by Ryan W. Cohen. Simple and to the point blog post by Ryan explaining how he discovered elevated iron levels in his blood, and the simple test he tried to find out why.
The Quantified Athlete by Matt Paré. Matt is a minor league catcher in the San Francisco Giants organization. In this post, the second in a series (read Part 1 here), Matt discusses how he became interested in tracking his biomarkers, and what he’s experimenting with.
What I Learned When I Stopped Wearing a Fitbit After Seven Years by Michael Wood. Michael writes up a brief post on how he felt when he was separated from his Fitbit activity tracker.
How I tracked my house movements using iBeacons by Joe Johnston. Joe uses a few iBeacons to find out where he spend time in his house. Fascinating idea, makes me want to play with this technology as well!
Visualizing a Simpler RunKeeper Training Plan by Andy Kriebel. Andy presented his running data, and how he uses a few tools to keep track and visualize his data as he trains for a marathon. Follow the link and you can see his Tableu workbook, which includes a screencast of his presentation, and links to his workflow.
I decided to take a peek at my Netflix viewing data by Reddit user AmericanPicker69. This enterprising individual decided to take a peak into his user account to understand his Netflix viewing habits. Turns our a simple copy/past is all you need to do to get the raw data. Who knew?!
My weight loss journey by Reddit user IMovedYourCheese. Loved this graph and the implementation of BMI categories, a moving average, and lower/upper bounds for weight loss. He even provided the excel template if you’d like to use it with your own weight tracking.
Have you registered for our QS Europe Conference? Makes sure to do so soon as early bird ticets (€149) are almost sold out. Register today!
Why Cities Need More Technology To Improve Low-Income Citizens’ Lives by Ben Hecht. Can technology create meaningful impact for the disadvantaged in communities across the United States? In this brief article, Ben Hecht describes a few exemplary projects, which are building and using technology to for social impact.
We are data: the future of machine intelligence by Douglas Coupland.
I sometimes wonder, How much data am I generating? Meaning: how much data do I generate just sitting there in a chair, doing nothing except exist as a cell within any number of global spreadsheets and also as a mineable nugget lodged within global memory storage systems — inside the Cloud, I suppose.
New open source uBiome github repository for data analysis tools by Alexandra Carmichael & Richard Sprague. Have you started testing your microbiome and want to do a more in-depth analysis? Check out this post and the open source tools.
You Shouldn’t Trust Me by Mike Lazer-Walker. A brilliant post by Mike describing a coffee tracking application that he released as both a paid and open source application.
It’s more important to me that we seriously think about our privacy, and what trust means in context of software that handles our personal data. We need to think about the repercussions of trusting large corporations that don’t have our best interests at heart and have no incentives or obligations to be transparent.
Track It! by Dave Mierau. A short post, but Dave does a great job of describing the power of monitoring and tracking. Go spreadsheets!
Currently Tracking by Chris Campbell. What is your tracking routine? In this post, Chris describes a day in the life of his quantified self. I’m sure you’ll learn about one or two new apps/tools. I did!
Carl Apstein: Annual Reports by Nicholas Felton. It’s no surprise that Mr. Felton is always on the lookout for Annual Reports from around world. In this post he posts a few photos from a hand-drawn report by the German zoologist, Carl Apstein, from the 1930s.
From the Forums
This Week on QuantifiedSelf.com
Our Data, Our Health: Thoughts on using mHealth for the Precision Medicine Cohort
Quantified Self Public Health: Stephen Downs on Building a Culture of Health
Runkeeper & Research: The Keeping Pace Study
In 2013, just prior to our our Quantified Self Global Conference, we asked conference attendees to send us examples of their own personal data visualizations that they found especially meaningful. We were blown away by what everyone shared with us. From visualizations of blood glucose readings to GPS traces and plots of time tracking and productivity, the range of visualizations was astounding (you can view some of those visualization by searching the blog for the QS Gallery tag).
This year, we sent out the request once again to attendees of our QS15 Conference and Expo. Once again, our inbox immediately started to fill up with images, graphs, and visualizations describing the tracking experiences of our amazing community. Today, we’re excited to start sharing those visualizations with you here.
Name: Beau Gunderson
Description: A homemade polysomnogram with a Zephyr Bioharness as the only data
Tools: IPython, matplotlib, pandas, seaborn, numpy.
Name: Shannon Conners
Description: This graph shows what initially looks like an interesting trend in my activity data. I seem to be less active during the summer months, but when I pair my activity and wear time for the BodyMedia FIT armband I used to generate the data, the real reason for the drop becomes clear. I’m wearing the armband less in the summer months to avoid upper arm strap tan! I know my own device usage patterns, so when I graphed the two measures together, it was immediately clear to me what was going on. To me, this is a simple example that illustrates one of the big challenges of looking at activity monitor data in the absence of data about device usage. Usage patterns can and do change over time and the reasons for these changes may not be as obvious as the change of the seasons. For example, something as simple as breaking the clip-on case you use to carry the phone that counts your steps could greatly impact how often you carry it, and therefore the quality of the data you collect. Some monitors don’t even record a usage metric with which to compare activity data. I like this graph as a reminder that interesting patterns may in fact be data collection or data quality issues in disguise.
Tools: BodyMedia FIT Core BW, JMP
Name:: David Korsunsky
Description: Mashing data from my favorite wearables, my medical records as well as data I track manually into a custom dashboard.
Tools: Heads Up Health is software that can enable anyone to create their own custom configurations.
Name:: Jo Beth Dow
Description: Trend analysis of my HRV over a 2.5 year period. Displays a stunning seasonal trend.
Tools: iPhone running SweetBeatLife app to measure clinical grade HRV on a daily basis.
Stay tuned here for more QS Gallery visualizations in the coming weeks. If you’ve learned something that you are willing to share from seeing your own data in a chart or a graph, please send it along. We’d love to see more!
On June 20th we’re inviting the public to join us for the first ever Quantified Self Expo. It’s going to be a full day of dedicated to showcasing amazing QS tools with multiple demos, talks, how-to sessions, and exciting experiences. But that’s not all.
We’re excited to host, as part of the Expo, an exhibition focused on data as art. In the words of our co-curators, Alberto Frigo and Jacek Smolicki:
Art of Self-Tracking is an exhibition gathering a number of international artists who use different personal data tracking techniques in their artistic practices.
Ranging from meticulously composed manual diaries, hand-drawn representations of every meal consumed on daily basis to sonification of geo-locational data and 3D renderings of shapes recognised in clouds, the exhibition aims to highlight the plurality of perspectives on self-tracking.
We’re honored to be hosting the following artists and their amazing work (which you can see a few previews of below):
Alberto Frigo (IT/SE), Brian House (US), Catherine D’Ignazio (US), Daniel Peltz (US), Davide Di Saró (IT/CA) & Kristy Trinier (CA), Elly Clarke (UK/DE), Ellie Harrison (UK), Giovanni Meneguzzo (IT), Ingrid Forsler (SE)
Borítás Viktor alias Iwan Wilaga (HU/HK) , Jacek Smolicki (PL/SE), Jacopo Pontormo (IT), James Pricer (US), Janina Turek (PL), Morris Villarroel (CA/ES), Stephen Cartwright (US), and Yann Vanderme (FR).
To see the artwork for yourself we invite you to join us on the 20th. It’s going be a wonderful event.
Enjoy this week’s list!
You’re invited to join us on June 20th for an amazing day of demos, talks, and sessions highlighting the very best of the Quantified Self at our QS15 Expo. Readers of What We’re Reading get a special discount. Just click here to get $10 off your ticket price.
We’ve received some amazing entries in our Future Normal QS15 Challenge, so amazing that we’ve extended the challenge a few days. If you’re reading this before Monday, June 1st make sure to enter nowfor your chance to win two free Ultimate Panels!
I’m the New CTO of HHS by Susannah Fox. So great to see this announcement. All of us at QS Labs have the utmost respect and admiration for Susannah and her dedication to positively impacting human health. Additional posts and articles about Susannah’s appointment can be found here and here.
As technology savvy as Susannah is, it is her capacity to hold a huge vision, and keeping patients at the center of that vision, that make her so deeply qualified for this job. No body asked me who the next CTO of the government was going to be, and frankly I was a little worried about who would be next. Bryan Sivak and Todd Park (her predecessors in this role) leave pretty damn big shoes to fill. Someone in the Whitehouse/HHS is casting a net wide enough to know who the really transformational thinkers in our industry are. – Fred Trotter
Special Report: Hacking the Human OS by IEEE Spectrum. A fantastic three-part report here by folks over at IEEE. This collection of articles, infographics, and op-eds is a must read.
Public Health and Tech: Long Lost Lovers? by Vanessa Mason. A short but nice article outlining how technology may interface with Public Health practices and program implementation. Great to see a mention our RWFJ supported Quantified Self Public Health Symposium.
The quantified self in a complex system: A systems perspective on mental workload by Steven Shorrock. A great post here by Steven concerning the role of quantitative information in dynamic and often complex human systems (like your workplace).
For these reasons, most numerical measures concerning human experience and system parameters should be treated as social objects. Any data on mental workload, sector capacity values, traffic numbers, or whatever, are a reason for a conversation, the start of a conversation – not an end point.
Apple Health App and My Quantified Self by Nadine Fischoff. One day Nadine realized her iPhone was keep track of her daily activity (steps and distance walked) so she decided to dive into the data to see what she could learn. With the help out our QS Access app (download it today – it’s free!) she was able to access, download, and analyze her data. What did she learn? Moving to New York City from Mountain View increased her daily walking 48%!
2014 Writing Progress by Ben Wilson. A great post here by Ben describing his writing progress over 2014. Ben tracked his goal of writing two novels in 2014, and ended up tracking over 90,000 words written.(Found via the always excellent Exist.io Blog.)
Withings Health Observatory: Blood Pressure by Withings. Great to see Withings has added blood pressure to their real-time data dashboards.
Visualizing the Quantified Self: Giving Form to Lifelogging by Fil Greenwich. A nice overview post of different data visualizations.
From the Forum
This Week on QuantifiedSelf.com
So much going on this week! We just announced and opened registration for our QS15 Exposition. If you’re in the Bay Area join us on June 20th for an amazing day of demos, talks, and sessions highlighting the very best of the Quantified Self. Readers of What We’re Reading get a special discount. Just click here to get $10 off your ticket price.
We also just announced the Future Normal QS15 Challenge. Thanks to our long time friends and QS sponsors InsideTracker, we’re inviting you to take part in an exciting challenge to develop new ideas and questions about what we can learn from unlocking the information stored in our blood. Click here to learn more and enter to win two free Ultimate Panels!
Now, on with this week’s list!
How accurate is the Apple Watch’s step counter and distance tracking? by Dan Graziano. Great article testing how accurate the new Apple Watch is versus other activity trackers and smart watches. It’s a short(ish) controlled experiment, but the initial results seem positive. Key takeaway: if you have an Apple Watch take the time to calibrate it!
Forget the Fitbit: Can Wearables be Designed for the Developing World? by Jessica Leber. Together with Frog and ARM, UNICEF is launching a “Wearables For Good” challenge to generate ideas and designs for new sensors and technologies that can be used in “resource constrained environments.” Check out the challenge website here: Wearables For Good.
Is the Wearable Health Movement Sustainable by Tim Bajarin. TL;DR: Yes.
With Great Data Comes Great Responsibility by Paz. Ownership, privacy, and longevity. These are the three topics taken on in this long, but well written article on data. If you’re working with or collecting a user’s data this is a must read. And if you’re sending your data to a service, you might as well read it too.
Data is Personal by Frances Angulo. A beautiful post by Frances about using a few simple tools to track anxiety, including a few wonderful visualizations. Once again, I’m astounding by the simple power of using a tool like Google Forms to ask oneself the question that matter.
This is what it is like to be charged by a hippopotamus. by Jer Thorp. Turns out it’s super scary and makes your heart rate jump through the roof. Make sure to click through to see and hear the visualization. It’s well worth it.
From the Forum
This Week on QuantifiedSelf.com
In our second episode of QS Radio we shake things up a bit. We start with a brief discussion by co-host Steven Jonas about his experiences using the SunSprite light tracker and what he’s been learning. Next up, we have a great Toolmaker Talk with Kevin Holesh, the creator of Moment for iOS. Moment is a self-tracking app that helps you track how much you use your iOS devices (iPhone or iPad). Lastly, we wrap up with a short discussion about some interesting news and tidbits about personal data, self-tracking, and quantified self. Links to everything we discussed are below. Enjoy!
What We’re Reading
- The End of Asymmetric Information
- Download Your Google Search History
- Impact of music streaming on my listening habits by Maciej Konieczny
- How We Are Measuring Happiness at Whitesmith by Daniel F. Lopes
- Tracking Joy at Work by Joe Nelson
Don’t forget to register for the QS15 Conference and Exposition. If you’re interested in Quantified Self, self-tracking, and personal data there is no better place to meet expert users, advanced toolmakers, and learn first-hand through our may talks, sessions, and demos. Register now!
The validity of consumer-level, activity monitors in healthy adults worn in free- living conditions: a cross-sectional study by Ty Ferguson, Alex Rowland, Tim Olds, and Carol Maher. A very interesting research study examining the accuracy of different consumer activity trackers when compared to “research-grade devices.” Free living only lasted a few days, but it’s a great start to what I hope to see more of in the research – actual use out in the wild.
The Healing Power of Your Own Medical Records by Steve Lohr. Steven Keating has a brain tumor. He also has over 70GB of his medical data, much of which is open and available for anyone to peruse. Is he showing us our future? One can hope.
Mr. Keating has no doubts. “Data can heal,” he said. “There is a huge healing power to patients understanding and seeing the effects of treatments and medications.”
Why the DIY part of OpenAPS is important by Dana Lewis. Always great to read Dana’s thoughts on the ever evolving ecosystem of data and data-systems for people living with diabetes.
Why I Don’t Worry About a Super AI by Kevin Kelly. I, for one, am super excited for advancements in artificial intelligence. There are some that aren’t that excited. In this short post our QS co-founder, Kevin Kelly, lays out four reasons why he, and maybe why all of us, shouldn’t be fearful of AI now or into the future.
Responding to Mark Cuban: More is not always better by Aaron Carroll. Earlier this week Mark Cuban started a bit of an kerfuffle by tweeting out, “1) If you can afford to have your blood tested for everything available, do it quarterly so you have a baseline of your own personal health.” What followed, and is still ongoing, is a great discussion about the usefulness of longitudinal medical testing. I’m not sure I agree with the argument made here in this piece, but interesting nonetheless.
My Quantified Email Self Experiment: A failure by Paul Ford. Paul takes a look at his over 450,000 email messages dating back 18 years. He find out a lot, but states that he doesn’t learn anything. I disagree, but then again, I’m not Paul. Still fascinating regardless of the outcome.
Filling up your productivity graph by Belle Beth Cooper. Want to understand your productivity, but not sure where to start? This is a great post by Belle about how she uses Exist and RescueTime to track and understand her productive time.
2014: An Interactive Year In New Music by Eric Boam. We’ve featured some of Eric’s visualization work here before, but this one just blew me away. So interesting to see visualization of personal data, in this case music listening information, turned into something touchable and engaging.
“Women and Children First” by Alice Corona. A fascinating deep data dive into the Titanic disaster. Was the common refrain, “Women and children first!” followed? Read on to find out.
HHS Expands Its Approach to Making Research Results Freely Available For the Public
European Food Safety Authority (EFSA) Grants Public Access to Data through Scientific “Data Warehouse”
FDA ‘Taking a Very Light Touch’ on Regulating the Apple Watch
Selling your right of privacy at $5 a pop
From the Forum
Enjoy this week’s list!
The inside story of how Apple’s new medical research platform was born by Daneila Hernandez. I know we’ve been talking a lot about ResearchKit lately, but I had to add this fantastic piece on Stephen Friend’s journey that lead him to help bring it out of Apple’s lab and onto our iPhones. Of particular interest was this sentence from a FOIA request on Apple’s meeting with the FDA in 2013:
“Apple sees mobile technology platforms as an opportunity for people to learn more about themselves. “
Your Data Is Not Your Life Story by Michael Humphrey. An interesting take on the influence of machines and algorithms on our ability to understand and tell the stories of our lives.
Data Privacy in a Wearable World by Gawain Morrison. Gawain lists five steps for companies to consider as they beocome the gatekeepers of our personal data. My favorite: “Set up an ethical body”
DJ Patil Talks Nerd to Us by Andrew Flowers. You may know DJ as the gentleman who coined the term “data scientist” or from his groundbreaking work at LinkedIn, or maybe even his new position as the deputy chief technology officer for data policy and chief data scientist at the White House. Regardless, this interview sheds some light on his new role and how he thinks about the power of data at the national level.
Wireless Sensors Help Scientists Map Staph Spread Inside Hospital by Scott Hensley. A great piece on a new research article the described a new digital epidemiology method used to track individuals and infection in a hospital. One can’t help but wonder about the future of this type of system for understanding healthcare interactions now that we have low-cost iBeacon, NFC, and RF technology embedded into our phones.
Sensored City by Creative Commons. Together with the Robert Wood Johnson Foundation and the City of Louisville, CC Science is creating an open-source project to map and visualize environmental data. So great to see this work getting out there.
Reflections on my ongoing diet and fitness project by Shannon Conners. Again Shannon wows us with her beautiful and thoughtful explanation on how tracking and visualizing her data has set her on a path to a healthy weight.
“I have now collected enough free-living data in my own n=1 study to quantify what works for me to lose weight and maintain in a healthy range for me — an understanding that largely eluded me up to this point in my life. Not surprisingly, I have converged on the same deficit strategy commonly employed in weight loss studies that treat people like caged rats, closely quantifying their intake and activity to prove that negative calorie balance is the critical factor that causes weight loss. I’m truly grateful that I didn’t need to live in a cage to learn what I have over the past few years. In many ways, learning what I have from my data has helped set me free.”
Tracking Joy at Work by Joe Nelson. Joe and his coworkers use Slack to communicate at work. He was wondering why sometimes things just weren’t working right so he created a tool to randomly ask himself and his coworkers how he they feel. Results are then displayed anonymously on a dashboard. So cool.
Dear Data by Giorgia Lupi and Stefanie Posavec. Two friends track one topic each week and send each other postcards with hand-drawn visualizations based on the data. Absolutely beautiful work.
Air Transformed By Stafanie Posavec with Miriam Quick. Two wearable data objects based on open air quality data: Touching Air (a necklace) and Seeing Air (glasses).
Laurie Frick – American Canvas. A great interview with our friend and data artist, Laurie Frick. Make sure to watch through to the end.
It’s Not Just the Watch: Apple Also Helping Cancer Patients
Americans Believe Personal Medical Data Should Be Openly Shared with Their Health Care Providers
What should we do about re-identification? A precautionary approach to big data privacy
Philosophy, bicycles and brains, opinions on tracking sleep, learning from actually tracking sleep, and visualizing work through vigilant self-report – all these and more in our reading list below. Enjoy!
Sleep apps and the quantified self: blessing or curse? by Jan Van den Bulck. Here at QS Labs, we’re very interested in how the academic and research world is colliding with those of us using tools of measurement previously restricted to science. In this Letter to the Editor, published in the Journal of Sleep Research, the author lays out an interesting set of opinions about the increasing availability and use of commercial sleep tracking devices. (You can access the full pdf here.)
Measuring Brainwaves to Make a New Kind of Bike Map for NYC by Alex Davies. Readers of the QS website may remember a great show&tell talk we featured back in May of 2014. In that talk, Arlene Ducao discussed her MindRider Project, an EEG tracking bicycle helmet. In this short piece, we learn that Arlene has continued this awesome work and has produced MindRider Maps Manhattan, exposing the brain data of 10 cyclists as they transversed New York City.
Big Data and Human Rights, a New and Sometimes Awkward Relationship by Kathy Wren. Earlier this year the AAAS Science and Human Rights Coalition held a meeting to discuss the intersection of personal data collection and human rights. This short article describing some of the key discussion points is a great place to start if you’re exploring what “big” and personal data means to you and your use of the tools and services that collect it. (Videos of the meeting are also available.)
How Theory Matters: Benjamin, Foucault, and Quantified Self—Oh My! by Jamie Sherman. A very interesting and thought-provoking essay here on the nature of self-tracking and data collection framed against the works of Michel Foucault and Walter Benjamin. We count ourselves lucky to have Jamie as an active member and observer of our QS community.
But taken together, Foucault and Benjamin suggest that the penetration of data into daily life is part of a larger shift underway, and that changes we can already see in social life, politics, and labor are not unrelated, but rather intimately linked.
Compulsory Quantified Self by Gwyneth Olwyn. I think it’s good practice to try and expose ourselves to all sides of the conversation around self-tracking, the positive and the negative. In this blog post Gwyneth describes a few ideas about the purpose and outcomes of self-tracking, especially when the self is superseded by the demands of others (such as in a workplace wellness program).
Sleep Data Analysis with R by Ryan Quan. Ryan has been tracking his sleep with the Sleep Cycle app for the last two years. In this excellent post he explores and plots his data (yay export!) to see when he goes to sleep, how long he sleeps, and what really makes up “quality sleep.” Love the fact that he included his R code and sample data. Go Ryan!
Quantifying Goals Using Key Performance Indicators (KPIs) by Bob Troia. No data in this post, but I found it particularly inspiring to see how Bob was planning on keeping track of his goals for this year. If you’re looking for ideas for tracking your 2015 goals and Key Performance Indicators this is a great place to start.
The Resume Of The Future by Eric Boam. The above is one of the two beautiful visualizations created by Eric to explore his daily work activity and interactions. This visualization shows what he was actually spending his time on. How did he collect the data? Well, he used the Reporter App to ask himself three questions: “where are you, what are you doing, and who are you with?” Make sure to read his post, he developed very interesting insights through collecting this data.
Weight Loss: What Really Works? by Emi Nomura and Laura Borel. Another fascinating data analysis project here by the Jawbone data science team. They examined the behaviors of a group of users who lost at least 10% of their starting weight vs users with no weight loss and found that the biggest difference in behavior was tracking meals.
Mapping my Last Two Years of Runs and Rides
While browsing the r/dataisbeautiful subreddit I stumbled upon this interesting tool/company that visualizes the maps of your runs and bike rides by connecting to your Runkeeper or Strava account. Above I’ve included my 2013 and 2014 maps. Clearly I need to find some new running routes in my neighborhood. (click through to enlarge)
QS Access Links
As part of our new work highlighting stories, issues, and innovations related to personal data access we’re going to start publishing a short collections links in this space. As this works grows be on the lookout for a new Access Newsletter from QS Labs.
Who Should Have Access to Your DNA?
What FDA developments in Diabetes mean for FDA approval in Digital Health
Open consent, biobanking and data protection law: can open consent be ‘informed’ under the forthcoming data protection regulation?
WTF! It Should Not Be Illegal to Hack Your Own Car’s Computer
Unique in the shopping mall: On the reidentifiability of credit card metadata
Majority of Consumers Want to Own the Personal Data Collected from their Smart Devices
Who Owns Patient Data
Los Angeles County Supervisors OK Creation of Open-Data Website