Cathal Gurrin is a researcher at Dublin City University and the University of Tsukuba. He’s also an expert in the field of visual and data-driven lifelogging. Since 2006 he’s collected over 14 million passively collected images from different wearable cameras. Add his other sensors and he’s nearing over 1TB per year of self-tracking data. In this talk, presented at our 2014 Quantified Self Europe Conference, Cathal describes what he’s learned over the last eight years and what he’s working on in his research group including search engines for lifelogging as well as privacy and storage issues.
We have a full set of Quantified Self meetups for the upcoming week. There will be 8 occurring in 4 countries.
Meetups featuring talks include the always excellent London group, as well as, the Washington D.C. meetup with show&tells on tracking one’s weight for over 26 years and daily routines. The Groningen meetup will feature a talk on continuous glucose monitoring and what someone found out from keeping a comprehensive log book for three months.
In Indianapolis, they’ll go over how to use Apple’s Healthkit for QS. Surely, the QS Access app will come up in discussion. The group in Tokyo will be having a group discussion to talk about what they are tracking. And Portland will have their monthly workgroup, where they will make progress on their self-tracking projects.
Saturday (November 22)
Also, check out these photos from last week’s meetup in Warsaw:
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.
“How can I define what makes me happy and what makes me sad, what is good for me?”
In 2012 Benjamin Bolland was finishing up his undergraduate degree and working on a new start-up. He found that his moods were constantly changing and wondered if there was something he could do to make sense of them as they moved “up and down.” He began tracking his mood with an simple self-designed Google Form. Each day at 11AM and 6PM he reported his mood on a 1-10 scale and wrote a quick descriptive note. After 1.5 years of doing this nearly every day he realized that he didn’t really know what was making him happy or sad so he decided to update his Google Form to include a variety of different categories that he thought might affect his mood including physical health, sport participation, and many others. In this talk, presented at the Berlin QS meetup group, Benjamin describes his process and how he’s used this mood tracking process to be more reflective and mindful during his daily life.
It’s commonly believed that we sleep away approximately a third of our lives. Is it good sleep? Does it help us refresh and regenerate? What can we do to make our time spent in bed even better?
Join us at our upcoming QS15 Global Conference and Exposition on June 18-20 in San Francisco to learn first-hand about how to track your sleep and benefit from your sleep data.
We’re excited to have our QS Washington DC meetup organizer, PhD student, and avid self-tracker, Daniel Gartenberg, sharing his deep knowledge of tracking sleep. Daniel has used multiple devices to find out what works and what helps him achieve a better night’s sleep, including the Sleep Smart Alarm Clock, Galaxy Gear watch, the Actiwatch (a research validated devices), and the Hexoskin shirt. We may even get a peek at the sleep tracking capacities of the Apple Watch.
Daniel’s Sleep Tracking session is just one of the many hands-on, up-to-date, expertly moderated sessions we’re planning for the QS15 Global Conference and Exposition. This year, QS15 is going to be two full days of self-tracking talks, demos, and in depth discussion, followed by a third day for a grand public exposition of the latest self-tracking tools. Join us at the Fort Mason Center on the San Francisco Waterfront. We’ve made some early bird tickets available for readers of the Quantified Self blog (for a limited time): Register here!
This week we have five meetups in four countries! The meetup in Warsaw will feature a show&tell on what can be learned from combining one’s genetic and microbiome data. The first QS group, Bay Area, will be having their meetup in Berkeley and will feature talks about running data and memorizing personal events.
After two very successful events, Vienna will be hosting their third show&tell. Copenhagen will feature a talk by Mette Dyhrberg, who once provided us with this excellent visualization. The Vancouver group is teaming up with a hardware-focused meetup for presentations on the world of personal data sensors.
To see when the next meetup in your area is, check the full list of the over 100 QS meetup groups in the right sidebar. Don’t see one near you? Why not start your own!
Monday (November 10)
Wednesday (November 12)
Friday (November 14)
Vancouver, British Columbia
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
On October 23rd, the QS Stockholm meetup group meetup collaborated with the Bionyfiken, a Swedish biohacking meetup, to host a meeting at the Karolinska Institute. We’re happy to share a recap from Mina Makar and Dina Titkova, a member and co-organizers of QS Stockholm .
The meetup was conducted in a very relaxed atmosphere starting with a small introduction by the organizers followed by a short video of Gary Wolf introducing Quantified Self. We then had a few presentations from our group members.
Tina Zhu is a PhD student at KTH with focusing on Biofeedback. She talked about her interesting project of visualizing self-tracking data in the form of a fish in an aquarium. It was very interesting to see such data representation being taken to another level which could be easier for some to accept, understand, and interact with. Learn more about her work here: http://bodyandnature.
Glenn Bilby is an experienced sport medicine specialist then took the audience on a journey of all the gadgets that he has been using over the last 20 years to keep track of his different activities. During his presentation, Glenn discussed different topics related to how to use the data generated from the different devices and concluded that there is still much to be done when it comes to adding more meaning to the data.
Fredrik Bränström and Tom Everitt started a very interesting platform using a new algorithm to visualize data and highlight links between variables. This method is designed to give users a different perspective on how their daily activities are associated to each other. Their platform is available for testing here: www.kaus.se.
Sina Amoor Pour presented his reflections on what biofeedback and biohacking are and background on the Bionyfiken group.
Chai demonstrated how different chips could be implemented into the human body in order to perform different activities. He spoke about the wide range of applications for such chips ranging from starting your own car or bike.
If you’re based in Sweden, don’t miss the upcoming QS Stockholm meetups for more inspiration and ideas.
“There was nothing in my life pushing me to to have these more intimate relationships, the few people I actually care about.”
When Akshay Patil was putting together the guest list for his wedding he realized that it had been a long time since he’d spoken with some of the the people he was inviting. Even with his good friends, he surprised by his lack of communication, his inability to stay connected. As anyone faced with this realization he decided to try and change, but the realities of life quickly crept back and as they say, old habits die hard. When he left his last job and began looking for projects to work on, this troubling area of his life crept back to the fore. Maybe there was something he could do better track and change his communication and relationships. Using his development skills, and the ability to gather data from his Android phone, he decided to build a system that helped him stay in touch with the people that mattered most to him. In this talk, presented at the New York QS meetup group, Akshay talks about what’s he’s learned from using this app, including when it fails.
Siva Raj was interested in lowering his blood pressure. With a family history of cardiovascular disease and heart attacks he was worried about slightly elevated blood pressure (pre-hypertension). As someone engaged with understanding and building fitness applications he thought he would be able to lower his blood pressure by staying on track with a regular exercise program that focused on cycling. Interestingly his blood pressure measurement didn’t respond to his constant exercise or weight loss. After reading more research literature about the link between fitness and cardiovascular health Siva decided to change his training to improve his fitness. He decided to incorporate a increased intensity into his routine. After a short period of time he had increases in this fitness and was able to observe the reduction in blood pressure he was looking for. In the video below, filmed at the Boston QS meetup group, Siva explains his methods and talks about how he was able to track his body’s response to different fitness routines.