Tag Archives: reading

What We Are Reading

We hope you enjoy this week’s list!

Articles
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.

Show&Tell
interstellar-hr-hrv-gsr-1024x635
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!

Visualizations
StressSnail
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!

From the Forum
Get feedback and advice back
Basis Peak
Multi-API services for health/fitness data
Mobile Health and Fitness Apps Privacy Study

This Week on QuantifiedSelf.com
Greg Schwartz: Quantified Dating
David Joerg: Building My Personal Operating System

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What We Are Reading

Enjoy this week’s list!

Articles
Flipping Primary Health Care: A Personal Story by Kedar S. Mate and Gilbert Salinas. We’re leading off this week with a fascinating case study that describes what happened when one patient, Gilbert Salinas, “flipped the clinic.” After deciding to accept fellowship that would move him from California to Cambridge, MA he worked with his care team to take control of many of the tasks typically performed in the clinic.

Most importantly, I feel happier and healthier, and I am amazed that I have been able to accomplish my goal of being healthy during this year away from my providers. It has transformed my sense of what is possible and has encouraged me to take further ownership of my health.

A Case for Autonomy & The End of Participatory Medicine by Hugo Campos. I’m constantly in awe of our friend and QS community member, Hugo Campos. As a leader in the fight for access to personal data (see this great NPR piece from 2012) he’s been an inspiration for our own ongoing Access Matters work. In this post, Hugo makes the case for focusing less of patient participation in the medical system, and re-orienting towards improving patient autonomy and self-determination.

Health Data Outside the Doctor’s Office by Jon White, Karen DeSalvo, and Michael Painter. In this short post, the smart folks at RWJF introduce the new JASON group report, Data for Individual Health, which

“[…] lays out recommendations for an infrastructure that could not only achieve interoperability among electronic health records (EHRs), but could also integrate data from all walks of life—including data from personal health devices, patient collaborative networks, social media, environmental and demographic data and genomic and other “omics” data.”

A Systematic Review of Barriers to Data Sharing in Public Health by Willem van Panhuis and colleagues. In this review article, the authors outline twenty specific barriers standing in the way of sharing data that could improve global public health programs. They include numerous examples of the technical, motivational, economic, political, legal, and ethical barriers that prevent more sharing across public health systems.

#WeAreNotWaiting at the Fall 2014 D-Data ExChange: The Stars Are Aligning by Mike H. QS Labs was unfortunately unable to attend the Fall 2014 D-Data ExChange, but were excited to read this great summary of the event.

Show&Tell
The Quantified Self and Humanities Best Friend by Kevin P. Kevin found out that he could track his dog, Lilo, along with himself when he went for walks and runs. In this short post he outlines his process, and the barriers he ran into, for collecting data from his different devices to show his progress on a recent 5k walk.

Follow-up study: on the working time budget of a university teacher. 45 years self-observation pdf hereby Dimitar Todorovsky. Dimitar is a recently retired researcher and professor of Chemistry and Pharmacy at the University of Sofia in Bulgaria. In this journal article he outlines his findings from tracking his time every day over his 45-year career. Most striking to me is that he averaged 10hr of work per calendar day for the entire 45-year period.

Visualizations
HR_proposal
Heart Rate (bpm) during marriage proposal by reddit user sesipikai. Going to Rome to surprise your fiancé to be? Why not record your excitement and nervousness by wearing a heart rate chest strap!


To Big to Fail by Nicholas Felton. In this great video presentation Nicholas Felton describes the process behind building the latest in his series of Annual Reports. You can also check out the full 2013 Annual Report here.

From the Forum
Counterintuitive HRV Measurements
Active, Athletic Folks With Asthma Tracking Their Performance
Mobile Health and Fitness Apps Privacy Study
OP Innovations Sensors
Hexoskin
Timer/logger/tracker–what kind of gadget am I looking for?

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What We Are Reading

Articles
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.

Show&Tell
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 Life Analysis Spreadsheet by Reddit user batting_1000. A really interesting example of using Excel to track various aspects of daily life. Make sure to click through for the example screen shots.

Visualizations
BasisInterstellarMy 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.

Seasonal-compliance1-1024x576Activity 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.”

From the Forum
Wearable for Stress – Olive
Necklace worn fitness trackers?
MoodTraces App
New Heart Rate Variability and Coherence Papers
Artistic Apps

This Week on QuantifiedSelf.com
Ben Finn: Improving My Sleep
Nan Shellabarger: 26 Years of Weight Tracking

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What We Are Reading

Have a great time exploring these links, posts, and visualizations!

Articles
At Quantified Self, I forget I have Parkinson’s by Sara Riggare. Sara is a longtime member of our worldwide QS community and this heartfelt post about her experience at our conferences was wonderful to read. Experience the conference yourself and meet Sara at our QS15 Global Conference and Exposition. Register here 

Standards for Scientific Graphic Presentation by Jure Triglav. Jure is a doctor, developer, and researcher interested in how data is presented in the sciences. In this post he goes back in time to look at previous standards for presenting data that have largely been forgotten.

Painting with Data: A Conversation with Lev Manovich by Randall Packer. In this great interview, researcher, artist, and visualization expert, Lev Manovich, explains his latest work on exposing a window onto the world through photos posted to popular social apps.

Big Data, LIke Soylent Green is Made of People by Karen Gregory. A thoughtful essay here on automation, algorithmic living, and the change in value of human experience.

“In the production of these massive data sets, upon which the promise of “progress” is predicated, we are actually sharing not only our data, but the very rhythms, circulations, palpitations, and mutations of our bodies so that the data sets can be “populated” with the very inhabitants that animate us.”

When Fitbit Is the Expert Witness by Kate Crawford. I almost didn’t include this article in this week’s list. The story has been circulated so many times around the web this week, mostly without any real thought or examination. However, I found that Kate Crawford did a good job putting this news in context without resorting to sensationalism.

How California’s Crappy Vaccination Policy Puts Kids At Risk by Renee DiResta. A bit of a sensational title, but a great post that uses a variety of open data sources to showcase a growing concern about childhood vaccination policies in California.

Show&Tell
How I Used RescueTime to Baseline My Activity in 2014 and Set Goals for 2015 by Jamie Todd Rubin. I’ve been a big fan of Jamie’s writing since I found it earlier this year. He’s voracious self-tracker, mostly related to his tracking and understanding his writing, and this post doesn’t disappoint.

Sleeping My Way to Success with Data by Pamela Pavliscak. A great post by Pamela here about her experience starting tracking her sleep with the Sleep Cycle app. A great combination of actual data experience and higher-level thoughts on what it means to interface with personal data. I especially love this quote referencing her experience interacting with other sleep trackers,

“And they are doing the same thing that I’m doing — creating data about themselves, for themselves.”

Visualizations
IntoTheOkavango
Into the Okavango by The Office for Creative Research. A really neat interactive project by researchers, scientist, and the local community to document an expedition into the Okavango Delta in Botswana.

Strava
A Day in the Bike Commuting Life by Strava. The data science team at Strava put together a neat animation comprised of one-day of cycling commutes in San Francisco. Unsurprisingly, the Golden Gate Bridge is quite popular among cyclists.

From the Forum
Sleep tracking for new parents
Different Approach to ZEO Headband
Hello Everybody!
MyStress
New Self-Quantifier

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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 had a lot of fun putting together this week’s list. Enjoy!

Articles
A Spreadsheet Way of Knowledge by Steven Levy. A few weeks ago we noted that it was the 35th anniversary of the digital spreadsheet. Steven Levy noticed too and dug up this piece he wrote for Harpers in 1984. If you read nothing else today, read this. First, because we should know where our tools come from, their history and inventors. And second, but not last nor least, because it has wonderful quotes like this:

“The spreadsheet is a tool, and it is also a world view — reality by the numbers.”

The Ethics of Experimenting on Yourself by Amy Dockser Markus. With new companies cropping up to help individuals collect and share their personal data there has been an increased interest in citizen science. A short piece here at the Wall Street Journal lays the groundwork for what may become a contentious debate between the old vanguards of the scientific institution and the companies and citizens pushing the envelope. (The article is behind a paywall, but we’ve archived it here.)

Better All The Time by James Surowiecki. I started reading this thinking it would be another good piece about the digitization of sport performance and training, and it was, but only partly. What begins with sports turns into a fascinating look at how we are succeeding, and in some cases failing, to improve.

Article 29 Data Protection Working Party: Opinion 8/2014 on the Recent Developments on the Internet of Things. Do not let the obscure boring title fool you, this is an important document, especially if you’re interested in personal data, data privacy, and data protection rights. Most interesting to me was the summary of six challenges facing IoT data privacy and protection. I’m also left wondering if other countries may follow the precedents possibly set by this EU Working Party.

30 Little-Known Features of the Health and Fitness Apps You Use Every Day by Ash Read / AddApp. Our friends at AddApp.io put together a great list of neat things you may or may not know you can do with various health and fitness apps.

Man Uses Twitter to Augment his Damaged Memory by John Paul Tiltow. Wonderful piece here about Thomas Dixon, who uses Twitter to help document his life after suffering a traumatic brain injury that severely diminished his episodic memory. What makes it more interesting is that it’s not just a journal, but also a source of inspiration for personal data analysis:

”Sometimes if I have like an hour, I’ll be like ‘How’s the last week been?’“ Dixon says. ”I’ll look at the past week and I’ll go, ‘Oh, okay. I really do want to get a run in.’ So I will use it to influence certain decisions.”

Patients and Data – Changing roles and relationships by David Gilbert and Mark Doughty. Another nice article about the ever-changing landscape that is the patient/provide/insurer ecosystem.

Show&Tell
The Quantified Anatomy of a Paper by Mohammed AlQuaraishi. Mohammed is a Systems Biology Fellow at Harvard Medical School, and he’s an avid self-tracker. In this post he lays out what he’s learned through tracking the life of a successful project, a journal publication (read it here), and how he’s applying what he learned to another project.

Calories In, Calories Out by (author unknown). A fascinating post about modeling weight reduction over time and testing to see if said model actually matches up with recorded weight. Not all math and formulas here though,

“I learned several interesting things from this experiment.  I learned that it is really hard to accurately measure calories consumed, even if you are trying.  (Look at the box and think about this the next time you pour a bowl of cereal, for example.)  I learned that a chicken thigh loses over 40% of its weight from grilling.  And I learned that, somewhat sadly, mathematical curiosity can be an even greater motivation than self-interest in personal health.”

Fitness Tracker on a Cat – Java’s Story by Pearce H. Delphin. A delightful post here about tracking and learning about a cat’s behavior by making it wear at Fitbit. Who said QS has to be serious all the time?!

Visualizations
MattYancey_Fitbit
100 Days of Quantified Self by Matt Yancey. Matt downloaded his Fitbit Flex data using our data export how-to then set out analyzing and visualizing the data. Make sure to click through for the full visualization.

IAMI_jpg
IAMI by Ligoranoreese. If you’re in San Francisco consider stoping by the Catherine Clark Gallery for this interesting exhibit. The duo, Ligoranoreese, created woven fiber optic artwork based on Fitbit data.

List of Physical Visualizations. I can’t say it any better than Mortiz Stefaner: “Remember that epic list of data sculptures and physical data visualizations? Well, it became more epic.

From the Forum
Anyone have a good way to aggregate and visualize data?
Questions about personal health tracking
Hello QS
Call for Papers: special issue of JBHI on Sensor Informatics
Sleep Tracking Device – BodyEcho

 

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What We Are Reading

We’re back after missing last week (sorry!) with a bit longer list than usual. Enjoy!

Articles
Thoughts on Quantified Self for Modifying Long Term Life Goals by Mark Krynsky. Mark, a member of our QS Los Angeles meetup group, is consistently putting together interesting ideas in the QS space. In this short post he explore how QS tools might be used to understand long-term life goals.

Open Data for Open Lands by Alyssa Ravasio. The value of data isn’t confined to what we can understand about ourselves. There is so much beneficial information out there, especially when it comes to public data. In this post, Alyssa makes the case for protecting and promoting open data ideas and concepts regarding out most precious public spaces – the national parks system.

Art at the Edge of Tomorrow: Lillian Schwartz at Bell Labs by Jer Thorpe. A wonderful biographical piece about Lillian Schwartz, a pioneer in the field of computational art and exploration.

Terms of Service by Michael Kelller and Josh Neufeld. A reporter and nonfiction cartoonist team up to use a comic to tell us about the new world of data and privacy we currently inhabit. Interesting format and compelling content!

Show&Tell
Narrative Camera by Morris Villarroel. Morris has been wearing a Narrative personal camera for six months. In this short post he explains what he’s learned and experienced over that time.

Where my 90 Hours of Mobile Screen Time in September Went by Bob Stanke. Bob used an app (Trackify) on his Android phone to track how much time he was spending on his phone and what apps he used the most.

Quitting Caffeine by Andrei-Adnan Ismail. Andrei wasn’t happy with his relationship with coffee and caffeine so he he decide to try and quit. Using tracking and really interesting use of “sprints” to gradually reduce his consumption, Andrei was able to quit. Great post here describing his process and the data he gathered along the way (including how his change affected his sleep).

Twitter Pop-up Analytics by Myles Harrison. Myles takes us through the process of downloading, visualizing, and analyzing personal data from Twitter.

Visualizations
EB_sleep_data_V3-05_1000
Seven Months of Sleep by Eric Boam. A bit of an old one here, but beautiful and informative nonetheless. Make sure to read the accompanying piece by Eric. (I’m also looking forward to seeing more about this dataviz of his Reporter app data soon.)

CalorieWeight_vizMy latest effort to visualize my calorie intake and weight loss by reddit user bozackDK. Using data collected from MyFitness pal, bozackDK has created this great visualization of his data. I asked what was learned from making this graph and received this wonderful response:

“I make graphs like these to keep myself going. I need some kind of proof that I’m doing alright, in order to keep myself wanting to go on – and a graph showing that I can (somewhat) stay within my set limits, and at the same time showing that it actually works on my weight, is just perfect.”

From the Forum
Using Facial Images to Track Mood?
Can You Track Inner Peace?
Different Approach to ZEO Headband
How Far Are You Quantified?
Google Fit

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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 weeks list. Feel free to submit articles, show&tell self-tracking stories, and QS data visualizations. Just email me!

Articles
Why can’t you track periods in Apple’s Health app? by Nat Buckley. With the recent re-release of Apple’s HealthKit enabled self-tracking and personal data system it no wonder that people are taking a long hard look at what data is being excluded. With the popularity of menstruation tracking apps (this app has nearly 30,000 ratings) it’s surprising this was overlooked. This excellent post is a must read on the topic.

Now That Cars Have Black Boxes, Am I Being Tracked? by Popular Science Editors. Questions and concerns about surveillance are becoming more commonplace. As someone who is looking to purchase a car in the next year or so I was happy to see this post come across my stream.

The Quantified Self community, lifelogging and the making of “smart” publics by Aristea Fotopoulou. I love it when people take a thoughtful look at the Quantified Self community and write about their experiences:

For me, the potential of QS for public participation lies in the show and tell meet-ups that constitute a central feature of this community. Meet-ups enable the exchange of stories about the success or failure of lifelogging practices; they allow people to connect and form synergies around common interests, and to explore wider questions such as personal data management and ownership. [...] members touch upon key political issues and create temporary spaces of dialogue: what happens to personal data, who has access to these data (is it private individuals, governments or corporations)? For what purposes (medical research)? And how can these data be interpreted (by algorithms, visualisations) and used to tell stories about people?

Stepping Down: Rethinking the Fitness Tracker by Sara M. Watson. Sara uses her personal journey of recovery from hip surgery to frame an interesting question: Should we trust our fitness trackers to prescribe movement goals?

Show&Tell
Practical Statistical Modeling: The Dreaded After-School Carpool Pickup by Jamie Todd Rubin. Jamie wanted to understand if there was a way he could reduce how much time he spent waiting in line to pick up his son from school. Why not track it and model it!

Bulletproof Diet and Intermittent Fasting: 1.5 Year Results by Bob Troia. Bob takes a deep dive into his data to see if this particular diet is having beneficial health effects. Click for the great data, stay for the wonderful discussion and very, very thorough write-up.

Visualizations


Quotidian Record by Brian House. I’ve been a fan of Brian House since his early days visualizing Fitbit data. I was reminded of this work during a conversation about geolocation data and thought it would be a nice addition to our visualization list.

KMcCurdy_SMVisualizing My Daily Self-Management by Katie McCurdy.

What does my daily medication and self-management look like? How could I visualize this regimen? How can I communicate the ‘burden’ and work of caring for myself?

I decided to draw pictures of the things that I need to do on a daily basis; that way I could show the workshop attendees what my day was like instead of just telling them.

JawboneTimetoEatIt’s Time to Eat by Karl Krehbiel. Karl, a data science intern at Jawbone used the data from their global community of users the determine the likelihood of food and drink consumption during the day. Really fun and interesting visualizations here.

From the Forum
Seeking opinions of diabetic self-trackers for non-profit project
Five Years of Weight Tracking
What Disclaimer should I use when making my personal #quantifiedself data public?

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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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