We’ve been holding Quantified Self Conferences since 2011. Every year since then we’ve been approached by scientists and researchers in the academic community to help them find a way to incorporate their work and their ideas into our structure. After a few years of holding back, listening, and watching the research community become engaged with other scientists and the real-world QS practitioners we’re ready to take that next step.
We are excited to announce today that we are inviting scientists and non-scientists to join a research oriented poster session at our upcoming Quantified Self European Conference on May 10th and 11th.
These sessions are a way for us to support interesting work that doesn’t fit into our established show&tell format, including research results from academic and scientific studies relevant to QS practitioners. Possible topics include (but are not limited to):
- Validity, reliability, usability, and effectiveness of self-tracking devices
- Experiment design
- Statistical and/or visualization methods
- Social and psychological investigation into self-tracking practices
- Social science research on the QS community
Our hope is that these posters and the conversations around them will help us (scientists and non-scientists) learn from each other, stimulate new ideas/projects, and to uncover new applications for the research findings.
How to submit a poster
The process is very simple. Simply send us a draft of your poster submission via email. We will be accepting submissions until April 14, 2014. For format and other info, please read the instructions below. The posters will be reviewed for content and relevance; if you would like to be involved with the review process, or have any questions, please contact us.
Posters should contain the following elements:
- Authors and affiliations
- QS Relevance
- Contact information. We recommend including a picture of yourself so others at the conference can find you, and, if applicable, your twitter account.
- You must use the A0 size (841 × 1189mm or 33.11 × 46.81 inches)
- A PowerPoint template is provided for you to use.
Remember to Keep It Short and Simple (KISS). We want to stimulate creativity and strongly recommend the use of tables, figures, and visualizations. For examples and design tips we recommend the following articles:
- Creating Effective Poster Presentations
- Advice on designing scientific posters
- Poster Presentation
- Designing Effective Posters
Dates & Deadlines
Deadline for submission is April 14, 2014. We will conducting reviews and informing submitters of acceptance on a continual basis. All submitters will be notified by April 21, 2014. We look forward to seeing your inspiriting projects and findings.
Another collection of thought-provoking items from around the web.
Articles & Posts
Plan to move from #quantified self to Qualified Self by Inga de Waard. Every now and then someone writes something that causes me to pump the brakes and really reflect on self-tracking and personal data collection. This is one of those time. Inga does a nice job here setting up her experience with self-tracking to understand her type 1 diabetes. She moves on to explore how “qualified data” might be a better source of information for personal growth, “I am more than my body, I am mind. So I want to understand more.”
The Bracelet of Neelie Kroes (in German) by Frank Schirrmacher. Can machines be trusted? Are we building and willingly wearing the handcuffs of the future by strapping tracking devices to our wrists? These questions are explored in this article. (If you’re like me you are probably wondering who Neelie Kroes is. Here’s some background info.)
Biggest Gene Sequence project to launch by Bradley J. Fikes and Gary Robbins. J. Craig Venter is at it again. Now that genome sequencing has passed the $1000 barrier he has set up a new company in order to recruit and sequence 40,000 people per year.
This Mediated Life by Christopher Butler. Another amazing piece of self-reflection spawned by the recently released Reporter App. Rather than reviewing the application, the author addresses what it means to self-track when we know we are our own observer. Do we bias our reflection and data submission when we know that each answer, each data point is being collected into a larger set? (This post reminded me of one of my favorite movie lines, “How am I not myself.” from I Heart Huckabees
The Open Collar Project. At a recent meeting I learned of this project to create an open-source dog tracking collar. Pet trackers are becoming more prevalent in the market, but the purpose of this project goes far beyond just understanding pet activity. I learned from the lead researcher, Kevin Lhoste, that they’re using this as a method to encourage and engage children in science and mathematics. Very neat stuff.
Twitch Crowdsourcing: Crowd Contributions in Short Bursts of Time [PDF] by Rajan Vaish, Keith Wyngarden, Jingshu Chen, Brandon Cheung, and Michael S. Bernstein. This research paper describes the results of a really interesting project to gather information from people using micro-transactions during the phone unlocking process. It appears that we can learn a lot from people in under 2 seconds.
The Open FDA. Not an article here, but I wanted to call attention to the new open initiative by the FDA. This new effort was spearheaded by Presidential Innovation Fellow, Sean Herron. If you’re interested in doing this type of work you can apply to be a fellow here.
Show&Tells (a selection of first person stories on self-tracking and personal data)
200 days of stats: My QS experience by Octavian Logigan. Octavian recounts the various data he’s collected including activity, sleep, email behavior, and work productivity. I really like how he clearly explains what tools he’s using.
A Year in Diabetes Data by Doug Kanter. We’ve featured Doug here on the blog before. From his amazing visualizations to his talks about his process, we’ve been consitently impressed and inspired by this work. In this post Doug recounts 2012 – “[...] the healthiest year of my life.” (Full disclosure: Doug sent me the poster version of his data and it is beautiful.)
This visualization comes to us from Tim Kim, a design student based in Los Angeles.
The map shows different collections and documentations made during my cross country trip. Posts made during the trip on various social media sites are orientated and placed by the geological locations. The states are elongated by purely how I felt about the duration of going across the specific state. For example, driving through texas sucked (no offense). Different facts are layered and collaged across the map to create and express a collective, over-all image of the trip. Some quantifiable information, some quantitative information to create a psych-geolocal map.
Thumbs Up Viz A really nice website that highlights and explains the good pieces of data visualization popping up all over the web these days.
From the Forum
Mark Drangsholt has been dealing with an issue with his heart since he was a young man. Since his early twenties, when he as diagnosed with paroxysmal atrial tachycardia he’s had to deal with irregular heart rhythms. In this talk Mark explains how the transition into adulthood negatively impacted his health and then how he used self-tracking and a focused athletic program to help him reduce his weight and improve his health. Most show&tell talks would end there, but Mark still had the irregular rhythm issue to deal with. After what he describes as an episode that made him think, “This is it. I’m going to die.” he decided it was time to apply his self-tracking process in order to understand his heart rhythm disorder and possible triggers. Mark also decided to go one step further and apply the principles of case-crossover design to his tracking methodology. Watch his talk below and keep reading to learn a bit more about why you might want to consider using case-crossover design in your self-tracking projects and experiments.
The following excerpt from the QS Primer: Case-Crossover Design by Gary Wolf provides a great background for his method:
Mark’s self-tracking data didn’t naturally fit with any of these approaches. To understand whether these triggers actually had an effect on his arrhythmias, he used a special technique originally proposed by the epidemiologists Murray Mittleman and K. Malcolm Maclure. A case-crossover design is a scientific way to answer the question: “Was the patient doing anything unusual just before the onset of the disease?” It is a design that compares the exposure to a certain agent during the interval when the event does not occur to the exposure during the interval when the event occurs.
Using this method, Mark discovered that events linked to his attacks included high intensity exercise, afternoon caffeine, public speaking to large groups, and inadequate sleep on the previous night. While these were not surprising discoveries, it was interesting to him to be able to rigorously analyze them, and see his intuition supported by evidence. “A citizen scientist isn’t even on the conventional evidence pyramid,” Mark notes. “But you can structure a single subject design to raise the level of evidence and it will be more convincing.”
“Personal experimentation is simply tracking, on a schedule.”
Ian Eslick is a scientist, researcher, and self-tracker. His unique history has led him down a path towards understanding what it means to understand yourself and your health in and outside the world of healthcare. Ian’s health history helped push him down this path. Since being diagnosed with psoriasis he’s been confronted with the difficult task of figuring out triggers, effects, and treatments as his symptoms changed over time. Ian, began to explore self-tracking by mentally noting what was going on in his life and his symptom severity. You would think that this “in my own head” tracking methodology would limit analytical capabilities, but it helped Ian create mental models that informed more consistent and rigorous tracking methods, as well as influenced his future research.
In this talk below Ian describes that research, both personal and community-based, that explored the concept of helping people learn how to create and engage with personal experimentation.
“What I came to in conclusion after all of this is that N of 1 is overkill for QS. It’s unnecessary level of rigor. Ninety-five percent confidence intervals are about scientific causal proof, but what I want to know is am I making a better decision. Is data improving my decision in some measurable way? Not is it a perfect decision or do I have proof. So we want to value personal significance over statistical significance. Statistical significance says that if I run this trial twenty more times I’m likely to get the same result, but what I want to know is should I keep doing this and in QS we’re never going to stop keep experimenting, in a way, because our life keeps going.”
An extra long list for you to this time. Enjoy!
Articles & Posts
Beyond the Data Portal by Jed Sundwall. The open data refrain has been taken up by non-profits, local, and national governments around the world. Have we questioned what it really means to be good data stewards? A very nice post here that opens up a discussion about the role of data librarians to augment simple access with human-powered information wayfinding.
Could Behavioral Medicine Lead the Web Data Revolution? by John W. Ayers, Benjamin M. Althouse, and Mark Dredz. If you can look past the slightly antiquated use of the term “web data” here you’ll see a good critique of the current methods in behavioral health science and the role of personal data in medical and behavioral research.
Little data: Tracking your life through numbers by Dominic Smith. A nice short piece here on the art behind self-tracking,
Critics might ask why we should care about the aggregated, daily routine of a man most of us will never never meet. But fans would argue that these reports aren’t merely novelties for the coffee table—they represent data as art, a single year of human life parsed into graphs and charts.
Fitness Trackers Could Boost Kids’ Health, But Face Challenges, Experts Say by Tia Ghose. Activity trackers are all the rage these days, but can they be used to track and understand children’s physical activity?
Questioning the Quantified Self as it Marches Towards Mainstream by Matt Stempeck. A very thorough recap of a talk by Natasha Dow Shull given at the MIT Media Lab. It covers the history of self-tracking and the current trend towards algorithmic selfhood. Great read.
When quantified-self apps leave you with more questions than answers by Brendan O’Connor. The author takes at self-tracking and personal data through the lens of the newly released Reporter app. Reading this piece left me wondering, are questions the prominent artifact of a self-tracking practice?
Dan Hon’s Newsletter By Dan Hon. I know you get enough email already, but this is an exceptional project by Dan to express his ideas in the form of a daily newsletter. Covering the vast arena of techno-culture, it’s a great addition to my inbox. See his thoughts on Quantified Self in issue #15.
Quantify Everything: A Dream of a Feminist Data Future by Amelia Abreu. A very interesting perspective on self-tracking and the Quantified Self movement by our friends at Model View Culture.
The Ethicist’s and the Lawyer’s New Clothes by I. Glenn Cohen [video]. An interesting lecture on the ethical issues surrounding the use and misuse of “smart clothing.”
Data Sharing Essay Competition by DNA Digest. A writing competition to explore themes around the positives and negatives of data sharing in the health research community.
Show&Tells (a selection of first person stories on self-tracking and personal data)
Quantify Yourself by Amo Utrankar. What happens when a medical student starts self-tracking so he can understand his future patients?
Between Week 1 and Week 4, my “compliance” fell from 96% to 63%. It takes a committed, conscious effort to record every meal, every vital sign, every exercise, every minute of the day. I hold a new-found respect for the diabetic patient who has to monitor his blood sugar, manage his appointments, and mind his meals; it’s a process that’s both distracting and exhausting.
I tracked every penny I spent for one year. Here’s what I learnt. by Todd Green. Ten lessons learned from a year-long meticulous tracking project.
I lost 1,000 hours of sleep in 1 year: My story as entrepreneur & new Dad by Nick De Mey. A father recounts his process of learning about his sleep, or lack thereof. (Editor’s note: Nick is a founding member of AddApp, a Friend of QS).
My Facebook Messaging History by Person and Time. A great visualization and conversation with open source code so you can make your own.
My Recent Exercise Log – Plotted. Another reddit user shares his exercise data from MyFitnessPal.
What can you learn from almost 3 years of Skype chat logs?. A simple, but nice word cloud visualization of chat logs.
In total there were 280114 words sent. Words that refer to oneself (such as: i, me, ich, my, mich, min, meiner, meine, meins, jag, mig, mir) were used 14995 times whereas words that refer to other people (like above list for others) were only used 6669 times! People in my Skype conversations like to talk about themselves… (which is mostly me. THERE, I did it again )
Selfiecity. An interesting exploration of new media visualization techniques and social media information processing by an outstanding group of researchers. Take a tour of the website then read Lev Monivich’s post about this new area of research and data visualization.
From the Forum
We’ve all come face to face with tracking some aspect of our life only to realize that we’re not quite sure how to get started. Enrico Bertini encountered this roadblock when he began thinking about tracking the amount of time he spends engaging in “focused work.” As an information visualization researcher at NYU he decided on a simple rule that would give him the most accurate data that represented his interests: if it wasn’t tracked then it wasn’t focused work. In this talk, given at the New York QS meetup group, Enrico explains his process and shares his findings (including some great visualizations).
Slides available here.
(Editor’s Note: Enrico also co-hosts a great podcast on data visualization and information design called Data Stories. I highly recommend listening. If you’re looking for a place to start try Episode 17: Data Sculptures.)
A big piece of our work at QS Labs is supporting our worldwide community through the over 100 Quantified Self Meetups (see our sidebar at right). At our local meetup in the Bay Area, and others we’ve had the pleasure of visiting, we are consistently observing that nearly half of the attendees are new to the Quantified Self. Considering this, Gary Wolf, our director and co-founder, gave a short presentation to introduce our work and how we see the Quantified Self as a cultural and technological movement. If you’re new here, or just want to reorient yourself, watch Gary’s excellent talk below.
“If I look at this, I have these memories, and I remember this was a good year.”
Collect it and forget it. This could be be hidden mantra of many people engaged with self-tracking, myself included. I will readily admit to buying a device or application with the hope that I can collect enough information to generate a grand insight at some mythical point in the future where the intersection of free time, analytical knowledge, and sample size magically coalesce. Ulrich Atz encountered the same problem. He was tracking, but soon lost sight of the purpose. Rather than giving up he started a new tracking project.
Ulrich started by building on the popular habit and tracking theory, Don’t Break the Chain, based on consistency in behaviors you care about. He identified six major categories he wanted to understand and pay attention to: his evening ritual, fitness, nutrition, learning, sleep, and travel. Rather than using an passive tracking system like Foursquare of Sleep Cycle, he decided to keep track of it by writing on a large wall calendar. In this presentation, given at the London QS meetup group, Ulrich describes his methods and what he learned from this year-long process.
Science. Someone makes an observation, creates a hypothesis, tests it, then analyzes the results against the hypothesis. Hopefully once a conclusion is reached it is tested again and again for validity and reproducibility. With self-tracking, the world of personal science and experimentation is opening up real-world personal laboratories to test the findings, claims, and promises available through the popular and scientific literature.
Nick Alexander is one of these self-experimenters. When he started to hear about thermodynamics and the effect of temperature on exercise and energy expenditure he decided to set up his own experiment:
I had been introduced to thermodynamics exercise research by former NASA scientistRay Cronise via Wired and the Four Hour Body. Ray makes an extraordinary claim (i.e. that exercising in a cold environment, especially in cold water, causes a large increase in calorie burn), and I was curious to see if it would work for me.
In this talk, given at the 2013 Quantified Self Global Conference, Nick explains his experimental setup and what he found after tracking over 30 runs and crunching the numbers. For a more in-depth discussion about his methodology and his findings I recommend reading his recaps.
This video is from our 2013 Global Conference, a unique gathering of toolmakers, users, inventors, and entrepreneurs. If you’d like see talks like this in person we invite you to join us in Amsterdam for our 2014 Quantified Self Europe Conference on May 10 and 11th.
We’ve collected another fun batch of reading for you. Enjoy!
High tech in vehicles puts drivers’ privacy up for grabs by Karl Henkel.The cars we’re driving are collecting, storing, and in some cases, transmitting all sorts of data. What are the implications of cars as computers?
Are Companies tracking us, or merely “observing” us? by James Robinson. Another privacy piece here. When large corporations collect consumer data are they able to understand us individually, or are they just making observations about general patterns? Don’t forget, we’ve been down this road before.
Here’s what happens when a data scientist goes to Disney World by Derrick Harris. Apparently the theme to start the list this week is consumer tracking. This article takes a look at the newly implemented “Magic Band” system at the Disney World Resort. Disney is clearly leading the field here, but experience augmentation based on personal data is coming very soon to a store near you.
NBA players start wearing wearable health trackers by John Comstock. Not a surprising move here by the the NBA to equip players with wireless healthy and activity tracking systems. This isn’t the first time we’ve seen self-tracking technology being adopted by professional athletes. I for one am looking forward to watching basketball games with integrated player data visualizations.
Self-surveillance: Should you worry or simply embrace your personal data? By Laurie Frick. A great piece here by our friend, Laurie Frick. Laurie is an artist based in Austin (and part of the Austin QS meetup group) that uses self-tracking data as the inspiration for her various artistic explorations. In this piece she explains her work and he feelings about self-tracking.
Home Automation is an EasyHard Problem by Scott Jenson. I’m a big fan of the Internet of Things and look forward to a more connected future. However, maybe our ideas about what is possible are misguided. In this short piece Scott explains that it’s possible we’re not properly classifying the actual problem at hand, “[...] humans are messy, illogical beasts and simplistic if/then rules are going to create a backlash against this technology.”
Summer Internship in Advanced Analytics. Our friends at Pew are looking for interns to work on advanced analytics and data science. We’d love to see a member of our QS Community help them out.
Visualizations of the Week
Eternal Portraits by Brian House. Facebook uses facial recognition algorithms to know what their users look like. At one point they exposed that data to users as part of the data export feature. Says Brian, “The information is unusable in its raw form without knowing the specifics of Facebook’s algorithm. But as an irrevocable corporate byproduct, the future implications of such data remain unclear.
The Formation of Love by Carlos Diuk. The Facebook data team crunched the numbers and started to learn what happens as users fall in and out of love.
Visualizing Health. A great new project from our friends at the Robert Wood Johnson Foundation and their collaborators at the University of Michigan. Browse the galleries to find scientifically vetted visualization techniques related a variety of health information situations.
From the Forum
Reporter App Question
Drowzy: app made by Board certified Psychiatrist and Sleep Medicine Expert
Fitness tracker and Jawbone Up data analysisa
Sentiment analysis on my own writing
Best iOS app to track water/coffee/alcohol intake?