Topic Archives: What We’re Reading
Enjoy these articles, examples, and visualizations!
OpenNotes: ’This is not a software package, this is a movement’ by Mike Milliard. I’ve been following the OpenNotes project for the last few years. There is probably no better source of meaningful personal data than a medical record and it’s been interesting to see how this innovative project has spread from a small trial in 2010 to millions of patients. This interview with Tom Delbanco, co-director of the OpenNotes project, is a great place to learn more about this innovative work.
Beyond Self-Tracking for Health – Quantified Self by Deb Wells. It was nice to see this flattering piece about the Quantified Self movement show up on the HIMSS website. For those of you looking to connect our work and the broader QS community with trends in healthcare and health IT you should start here.
So Much Data! How to Share the Wealth for Healthier Communities by Alonzo L. Plough. A great review of the new book, What Counts: Harnessing Data for America’s Communities, published by the Federal Reserve Bank of San Francisco and the Urban Institute. The book is available to read online and in pdf format.
The Ultimate Guide to Sleep Tracking by Jeff Mann. A great place to start if you’re interested in tracking sleep or just want to learn more about sleep tracking in general.
What RunKeeper data tells us about travel behavior by Eric Fischer. We linked to the recent collaboration between Runkeeper and Mapbox that resulted in an amazing render of 1.5 million activities a few weeks ago. The folks over at Mapbox aren’t just satisfied with making gorgeous maps though. In this post, Eric, a data artist and software developer at Mapbox dives into the data to see what questions he can answer.
General Wellness: Policy for Low Risk Devices – Draft Guidance for Industry and Food and Drug Administration Staff . On Friday, January 16, 2015, the Food and Drug Administration released a draft of their current approach to regulating “low risk products that promote a healthy lifestyle.” These guidelines point to a stance that will allow many of the typical self-tracking tools currently in use today to remain outside the regulations normally associated with medical devices. (A quick overview of this document is also available from our friends at MobiHealthNews)
The Great Caffeine Conundrum. A wonderfully thorough post about using the scientific process, statistics, and self-tracking data (Jawbone UP) to answer a seemingly simple question, “Does eliminating caffeine consumption help me sleep better?”
Four Years of Quantified Reading by Shrivats Iyer. Shrivels has been tracking his reading for the last four years. In this post he explains his process and some of the data he’s collected, with a special emphasis on what he’s learned from his 2014 reading behavior.
Pretty Colors by Chanlder Abraham. Chandler spent his holiday break exploring his messaging history and creating some amazing visualizations. Above you see a representation of his messaging history with the 25 most contacted people since he’s began collecting data in 2007.
Heart Rate During Marriage Proposal by Reddit user ao11112. Inspired by another similar project, this ingenious individual convinced his now fiancé to wear a hear rate monitor during a hike. Unbeknownst to her, he also proposed. This is her annotated heart rate profile.
Help CDC Visualize Vital Statistics by Paula A. Braun. The CDC has a new project based on the idea that better visualization can make the data they have more impactful. If you’re a data visualizer or design consider downloading the CDC Vital Statistics Data and joining #vitalstatsviz.
From the Forum
Enjoy the first What We’re Reading post of 2015!
Wearable Devices as Facilitators, Not Drivers of Health Behavior Change by Mitesh Patel, David Asch, and Kevin Volpp. This opinion piece seeks to describe the reasons why currently available health wearables are not “bridging the gap” between tracking and changing behavior.
Big Data Not A Cure-All in Medicine by Amy Standen. This story, which first appeared on All Things Considered, sheds some light on concrete examples of how data can be used to treat medical conditions, and the current roadblocks in place.
The Smart, Angry Home by Emily Anthes. Smarter homes, smarter grids, and more data about our energy use is undoubtably on the horizon. In this piece, Emily Anthes describes how providing data back to individuals about energy use, especially in multi-tenant dwellings, can be a source of tension.
Thoughts on the Quantified Self by Kevin Ripka. I really enjoyed this short post about the author’s reactions to Quantified Self. I was especially interested in his description of the “Four Types of Projects” that he believes one can undertake when self-tracking.
What 2439 Reports Taught Me by Sam Bev. Sam has been using the ReporterApp over the last year. Since he began he’s amassed over 2400 reports, and those have provided some interesting insights into his own life. Read this great post and make sure to visit his website where his reports are made visible.
Seen, Read 2014 by Steven Soderbergh. Steven Soderbergh is an acclaimed writer and director, who has been tracking his media consumption for a few years. This post chronicles the books, plays, TV, movies, and records he consumed during 2014.
Map Your Trips Using Pics From Your Phone by Marco Altini. In this how-to post Marco lays out a fun method for tracking travel and location using only the photos you take with your smart phone.
We’ve put together an extra-long list for our last What We’re Reading of 2014. Enjoy!
Medical Inhalers To Track Where You Are When You Puff by Alison Bruzek. We’ve been following Propeller Health (nee Asthmapolis) for quite a while and this piece does a good job outlining their technology and promise.
How Self-Tracking Apps Exclude Women by Rose Eveleth. A great article on the issues brought on by the gendered design of self-tracking tools and applications. Good to see thoughts and experiences from some of our QS community members included in the piece. (If you’re a woman interested in women’s only QS meetups there are groups in New York, Boston, and San Francisco.)
The Echoes of Hearts Long Silenced by Ron Cowen. Humans have been curious about the sounds our bodies make for centuries. What could we learn from tracking and recording those curious buh-bumps? Sprinkled throughout this great article are examples of the the power of hearing and recoding the human heart.
The Genetic Self by Nathaniel Comfort. A great longer read on the ever expanding role personal genetics can have on our life, especially our health.
This brave new world need only be dystopian if we surrender our agency. If we are aware of the exchanges we are making and how our information is valued—if we are alert to the commodification of personal data—we can remain active players instead of becoming pawns.
More Data, Fewer Questions by Jer Thorp. “Every headline about data from the NYTimes containing a question, from 2004–2014.” (Part of an outstanding collection of predictions for the future of journalism in 2015] curated by the Nieman Lab.)
Dada Data and the Internet of Paternalistic Things by Sara M. Watson. A great piece of speculative fiction here that “explores a possible data-driven future.”
Tech Giants Move to Protect Wearables by Ashley Gold. With more wearables and QS tools capturing personal health data there is increasing scrutiny on privacy and protection, especially at the federal level.
Make Your Own Activity Tracker by Young-Bae Suh. Want to track your activity, but also love DIY projects? This is the one for you. A great walk through, including sample code, to get you up and running with a wrist-based activity tracker.
Enviro-Trackers Are a New Gadget Trend. What Do We Do With Them? by Margaret Rhodes. What can we do with personal environmental data? Margaret explores this question in the wake of the new devices currently available and being developed to track the world around you.
Vicious Cycle by Patt Virasathienpornkul. A fun student project that imagines a close-loop system of calorie consumption and expenditure.
Music Records by Salem Al-Mansoori. A wonderful deep dive into eight years of music listening history. Salem supplements the raw listening data with additional information and creates an amazing set of visualizations to answer questions such as, “Where do the artists I listen to come from?” and “How are my tastes changing over time.”
Half a Year with Dash by Colin Sullender. When the Dash OBD tracking device connected with the IFTTT service in mid 2014 Colin began logging each of this car trips. In this post he gets into the data to see what he can learn from his driving data.
Superpowering Runkeeper’s 1.5 Million Walks, Runs, and Bike Rides by Garrett Miller. The folks at Mapbox have done it again by improving on their last map collaborations with Runkeeper. Make sure to poke around in the large map to see where people are running, riding, and walking in your area. Also see this interview/article if you’d like to learn a bit more about the project.
A Year in Moves Data by Patrick Maloney. Patrick graphed his tie spent at time and at work by access his Moves data.
Crowdsourcing a Runkeeper Dashboard by Patrick Tehubijuluw. Patrick built a nice overview data dashboard to explore his Runkeeper data. If you’re a QlikView User you can download and play with your own data.
Tell, Don’t Show by John Pavlus. Data dashboards are all the rage in our mobile-focused personal data world, but do they do a good job conveying information? John Pavlus argues that “data verbalization” is the next big user experience.
From the Forum
Understanding Goal Setting and Sharing Practices Among Self-Trackers
Wearable Timelapse Camera? (For time management)
New book about Quantified Self, called Trackers
Determine your Fitbit stride length using a GPS watch
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
Enjoy this week’s list!
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.
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.
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
Timer/logger/tracker–what kind of gadget am I looking for?
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.”
Have a great time exploring these links, posts, and visualizations!
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.
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.”
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.
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.
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 had a lot of fun putting together this week’s list. Enjoy!
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.
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?!
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 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.
From the Forum
Anyone have a good way to aggregate and visualize data?
Questions about personal health tracking
Call for Papers: special issue of JBHI on Sensor Informatics
Sleep Tracking Device – BodyEcho
We’re back after missing last week (sorry!) with a bit longer list than usual. Enjoy!
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!
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.
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.)
My 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.”