Steven Jonas

QS Portland co-organizer
Steven Jonas
Organizer of Portland meetup.

What We Are Reading



His Doctors Were Stumped. Then He Took Over by Katie Thomas. David Fajgenbaum, a medical student, discovered that he had Castleman disease, a hard-to-classify condition that sits between cancer and immune disorder which kills a third of patients within five years of diagnosis. Like most rare diseases, he found very little about it in the literature. It’s hard to fund research for a disease that affects so few (though legislation like the Orphan Drug Act helps). Fajgenbaum was tenacious in doing his own research and was willing to experiment on himself. By keeping copious records of his condition, including the T cell and VEGF levels in his weekly blood work, he may have made a breakthrough. Again, this breakthrough may help a small number of people, but here’s the thing about rare disease: there is a lot of them. According to the article, 10 percent of the population are afflicted with one of 7,000 rare diseases. With a group that large, we need alternate methods for doing research that does not rely on large sample sizes. -Steven (Thanks to Gwern)

The Usefulness of Useless Knowledge by Abraham Flexner. Princeton University Press has just reissued this classic essay by the founder of the Institute for Advanced Study, with a new companion essay by the physicist Robbert Dijkgraaf. I’m going to buy the book, but you don’t have to do that to read the original essay, with it’s terribly relevant opening paragraph: “Is it not a curious fact that in a world steeped in irrational hatreds which threaten civilization itself, men and women – old and young – detach themselves wholly or partly from the angry current of daily life to devote themselves to the cultivation of beauty, to the extension of knowledge, to the cure of disease, to the amelioration of suffering, just as though fanatics were not simultaneously engaged in spreading pain, ugliness, and suffering?” -Gary

Total recall: the people who never forget by Linda Rodriguez McRobbie. This article looks at a small group of people with an ability called highly superior autobiographical memory. These are people who can recall, with amazing clarity, specific details from every day of their life. It’s a fascinating read, but there are two details that I want to make special mention of. One is that this doesn’t a special talent people are born with, but, rather, it was a conscious decision they made early in life. The second is that this group has certain mental habits that I recognized from my attempt to memorize days from my daybook. Unlike most people, they actively organize their memories, tying them to the calendar. For instance, they can cycle through memories to figure out their favorite Tuesday. Memories exist in relation to one another in time. Another is that they keep the memories and their relationship between one another alive through constant repetition throughout the day. This suggests to me that with spaced repetition systems, one could train themselves to have a similar ability to remember their life. -Steven

What Happens When You Mix Java with a 1960 IBM Mainframe by David Cassel – This short, amusing piece about the improvisational talent of government fix-it artists, focused on an engineer for the US Digital Service named Marianne Bellotti, describes how they manage to connect ancient databases to modern web services, using methods that will mostly remain undocumented for the protection and safety of all concerned. As Bellotti says: ““The systems that I love are really the systems that other engineers hate,” Bellotti told the audience — “the messy, archaic, half chewing gum and duct tape systems that are sort of patched together. Fortunately, I work for the federal government, so there’s really no shortage of things like that for me to play with.” -Gary

When Things Go Missing by Kathryn Schultz. There are two types of loss that I hear described by people in the Quantified Self community. The first is the loss of existing data from, say, a corrupted hard drive, or a service that folds without notifying it’s users and allowing them to download their data. The other type of loss is the missed opportunity to track something that is now in the past. Not just the steps missed by a dead fitbit, but sleep before consumer sleep trackers existed. It’s a bit odd that the same emotion is invoked by two very different situations. In this essay, Schultz explores the concept of loss, from the trivial to the life altering. It seems to be our nature to hold on to things. Life logging could be seen as a desperate pencil rubbing of experiences before they pass. As Schultz puts it, “When we are experiencing it, loss often feels like an anomaly, a disruption in the usual order of things. In fact, though, it is the usual order of things. Entropy, mortality, extinction: the entire plan of the universe consists of losing, and life amounts to a reverse savings account in which we are eventually robbed of everything. Our dreams and plans and jobs and knees and backs and memories, the childhood friend, the husband of fifty years, the father of forever, the keys to the house, the keys to the car, the keys to the kingdom, the kingdom itself: sooner or later, all of it drifts into the Valley of Lost Things.” -Steven

Design Beyond the Numbers by Elisabeth van Dijk & Wijnand IJsselsteijn. This paper from the Eindhoven University of Technology is an astute examination of the motivations of self-trackers when they share their data over social media. Despite a reputation of oversharing, most people are careful of what, how and to whom they share their personal data. We are considerate about wasting other people’s time with low-value content and look to find “true peers” for whom the information has greater relevance and less likely to be rebuked. This is an important read for any QS toolmaker for building tools that help people get more from their data by sharing it effectively. -Steven

Show & Tell

This Is What Happens to Your Body on a Thru-Hike by Kyle Boelte. Kyle was already in good shape, but then he hiked over 486 miles on the high-altitude Colorado Trail in just under a month and compared his blood work before and after. Looking at body composition, resting heart rate, blood sugar, cortisol, and testosterone, the results moved in the expected direction, but the degree of change is still astounding. One metric that was new to me is the crossover point for heart rate where fat and carbohydrates are burned equally (As one’s heart rate increases, a greater percentage of carbs is burned). Kyle’s crossover point went from 153 beats per minute to 168. As Kyle joked to his wife, “I should start a business called 8-Hour Abs. Really, just eight hours a day is all it takes!” -Steven (Thanks to Richard Sprague)

Train for Strength or Endurance? by Laila Zemraini. Laila wanted to see if she benefited more from endurance or strength-based exercises. She alternated focusing on each category and looked at the rate of progress. In finding that she responded better to strength-based exercises, she found evidence for why that would be in her 23andMe data. -Steven

Finding out more about me, for free! by Matt Macdonald-Wallace. Matt was uncomfortable with entrusting his QS data to a “corporate organisation who could potentially profit from it”. He shows how he set up his own personal data server with a dashboard by using Connector DB, which bills itself as a “open-source platform for Quantified Self and IoT.” -Steven

College Performance by Tiffany Qi. When Tiffany started college, she assiduously tracked how she spent her time in Google Calendar. Now that she’s graduated, she looks at how the way she spent her time changed over the course of four years and the impact it had on her grades.

Data Visualizations

image (6)Gerrymandering in NC, or, A Tale of Two States by Jeb Stuart. A well-employed data visualization or metric can bring a topic into sharp relief. So it is here with an analysis of gerrymandering in North Carolina. Stuart looks at the number of wasted votes in elections for North Carolina representation in the U.S. House of Representatives. What is a wasted vote? When a candidate wins, all of the votes for that candidate above 50% are considered wasted (those votes could have been used in neighboring districts if the lines were drawn differently). The resulting graph shows how extreme this effort to sequester voters really was. -Steven

P-BirdsNA_10292015Birds of North America. This came out a couple years ago, but I just stumbled across it and spent a good ten minutes looking at all these birds. I loved looking at the variation in body and bill shapes, as well as the similarities that warranted grouping certain species together. This is a product page for a poster, but thankfully, you are able to zoom in and explore. -Steven

tumblr_ol3hg3dcUQ1qf3gj0o1_1280 (1)Seeing Me seeing by Simon Flühmann. I came across this visualization of a Swiss person’s Moves data on Tumblr. Unfortunately, there’s not a lot of context, but I love this type of location data visualization. -Steven

Come to QS17

Our next conference is June 17-18 in lovely Amsterdam. It’s the perfect event for seeing the latest self-experiments, debating the most interesting topics in personal data, and meeting the most fascinating people in the Quantified Self community. There are only 13 discounted tickets left. We can’t wait to see you there.

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Dispatch from QS Dublin: Results from a QS Community Survey

Today, we have a guest post from Justin Lawler, an organizer for the active and excellent Quantified Self group in Dublin, about a recent meetup. If you are a QS organizer, feel free to contact me about writing a recap of one of your events. -Steven

Recently, the Dublin Quantified Self meetup group gathered at the Dublin Science Gallery where Jenn Ryan presented the results from a recent survey on people’s motivations for tracking. We had an engaged group of people with health and wellness backgrounds, students, and the merely curious to discuss the current state of Quantified Self and how it’s impacting health.

Quantified Survey & The Potential of Personal Data in Healthcare

Jenn carried out the survey as part of her MSc thesis at University College Galway, trying to understand the motivations of those that track. A fitness instructor, Jenn is very conscious of public health and is always looking for new tools she can use with clients.

Some key insights from the survey:

  • A wide range of tools being used – from fitness trackers to phone apps to pen & paper.
  • Motivations for self-tracking included fitness goals, to tackling chronic diseases to self-knowledge & curiosity.
  • People found that the process of self-tracking was very useful for motivating behaviour change.
  • People found that once they started tracking biometrics, they didn’t stop once it became a habit.
  • People are not too concerned about the confidentiality of the data.
  • Overall people are happy with the tools we have.

Some charts from the survey:





“It is like when you are driving a car and you see the fuel gauge. If you couldn’t see the fuel gauge you would just drive on, but because you see it, you say ‘oh I am running low on fuel’ so I suppose if you see your weight going up or down, you can take action” -Survey Participant

Since survey responders were from the QS community, it wasn’t a diverse/cross-population sample. The respondents were high socio-economic status, educated, self-driven & curious. In other words, early adopters. There is still plenty of room for deeper analysis into self-tracking in wider population groups [See this Pew Research study for a view of the general public in the U.S. -Steven]

Jenn notes that there is huge room for growth as wearable trackers move to the early majority stage, as tools become more passive, easier to use and give more useful actionable insights. The Quantified Self movement will play a big part in the future of healthcare, as well as, efforts like the Institute of Medicine’s Learning Healthcare System which help healthcare iterate to provide better care.

Here is Jenn’s full presentation from the event:

You can follow the QS Dublin on their blog. If you live near Dublin, you can find out when their next meetup will be.

QS17 Tickets

You can meet Justin and other QS Dubliners at our next conference on June 17-18 in lovely Amsterdam. It’s a perfect event for seeing the latest self-experiments, debating the most interesting topics in personal data, and meeting the most fascinating people in the Quantified Self community. There are only a few discounted tickets left. We can’t wait to see you there.


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Meetups This Week

A great group of Quantified Self meetups are occurring this week. The group in Hamburg will have their meeting in conjunction with Social Media Week. The group in Dublin will be focusing on gut health, with a talk on stool analysis and another on gut hormones. Austin will welcome Dr. Bruce  Meleski to speak about techniques for increasing resiliency. Finally, Groningen will have talks about newborn tracking and trying to learn about happiness through self-tracking.

Tuesday, February 28
Hamburg, Germany

Wednesday, March 1
Dublin, Ireland

Thursday, March 2
Austin, Texas
Groningen, Netherlands

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! If you are a QS Organizer and want some ideas for your next meetup, check out the myriad of meetup formats that other QS organizers are using here.

Get your tickets for QS17

Our next conference is June 17-18 in lovely Amsterdam. It’s a perfect event for seeing the latest self-experiments, debating the most interesting topics in personal data, and meeting the most fascinating people in the Quantified Self community. There are only a few discounted tickets left. We can’t wait to see you there.

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Laila Zemrani: Training for Strength or Endurance?

While it is clear that exercise is beneficial, how does one decide what to do to get and stay fit? When Laila Zemrani surveyed people at the gym, she found that a majority don’t decide at all. Sixty percent didn’t know why they were doing a particular exercise. And of those, 50% admitted to merely copying whatever their neighbor was doing.

Laila spoke recently at a QS meetup in Boston about how she tried to be more intentional in her choice in exercise. In reviewing the number of available exercises, she was able to put them into two buckets: strength and endurance. She decided to track the effectiveness of each training regimen by focusing on a single metric and watching its progress. For strength, she focused on body fat ratio. For endurance, she looked out how long it took her to run the same distance. She then alternated her training every three months or so, focusing on one or the other.

Laila Zemrani speaking at QS Boston

Laila Zemrani speaking at QS Boston

Here’s what she found. When she focused on strength training, her body fat ratio improved. For instance, in one three month period it went from 29% to 25%. This type of improvement repeated itself a number of times. However, when she focused on endurance, she did not see improvements in the time it took her to run a certain distance.

Using a Fitbit Aria, Laila tracked body fat while alternating training regimens.

Laila tracked body fat with a Fitbit Aria scale.

It’s hard to know what conclusion to draw from these results. Are these the right metrics for assessing performance? What does it mean to respond more to strength than endurance exercise? However, the question of why Laila seemingly responds better to strength-based exercises may be found in her genetics. She used a DNA test from 23andMe and the results suggested that she shows a propensity toward building fast-twitch fibers which allow for better performance at explosive activities, such as sprinting or weight-lifting. On the flip side, people who are more proficient at building slow-twitch fibers tend to do better at endurance-type activities such as running long distance. Everyone has a combination of the two types of muscle fiber, but the ratio seems to be correlated with performance, depending on the type of activity.

Screenshot from Laila's 23andMe account.

Screenshot from Laila’s 23andMe account.

With these results, Laila decided it made sense for her to focus on strength-building exercises, since it seems that her body was built for that type of activity. Laila feels that having this information is allowing her to personalize her regimen and be more intentional about how she exercises, rather than be too influenced by the latest fads in fitness.

It can be debated whether it makes sense to focus on strength as opposed to endurance, depending on which one you see progress in. For Laila, the appearance of progress is important psychologically, in that it is easier to motivate herself if she sees improvement. There could be a downside to appearance of quick improvement, though. Ralph Pethica also uses genetic data to inform his training. He is the opposite of Laila in that his body is better suited for endurance exercise. What he finds, though, is that he improves and adapts too quickly and sees his performance plateau. To overcome this, he found that switching between steady-state training sessions and high-intensity intervals minimized the time he spent plateaued.

Training with knowledge of your genetic background is still a nascent practice. It’s still unclear how this information can and should be used. Useful ways to take advantage of this genetic information is still being tested and developed, but progress could be hastened if more people knew if they had more slow-twitch or fast-twitch muscle fiber. If this awareness is increased, it could lead to better strategies to get more out of exercise and reduce frustration and, hopefully, abandonment of the gym.

You can watch Laila’s entire Show&Tell presentation that she gave at a QS Boston meetup. You can follow up with Ralph’s Show&Tell from the QS Europe conference.

Tools used:
Fitbit Aria Wi-Fi Smart Scale

23andMe DNA Test – Health + Ancestry

QS17 Tickets are Available

Our next conference is June 17-18 in lovely Amsterdam. It’s a perfect event for seeing the latest self-experiments, debating the most interesting topics in personal data, and meeting the most fascinating people in the Quantified Self community. There are only a few early-bird discount tickets left. We can’t wait to see you there.

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Stefano Schiavon: Using Data to Understand Personal Comfort

Stefano Schiavon is an assistant professor and researcher interested in sustainable building design. As he told us at last month’s Quantified Self meetup in Berkeley, California, “I am Italian. I love architecture. And I think buildings are beautiful.”

One goal of building design is to increase individual comfort. However, this poses a problem. Everyone is different. For instance, what should the temperature be set at? There is no one temperature that is comfortable for everyone. It doesn’t work to try find a temperature that is pleasant to the largest number of people. As Stefano puts it, it is like going around and measuring everyone’s foot to get an average, say 9, and then dictating that everyone wear size 9 shoes to the office.

So how does this connect with Quantified Self? Stefano and his colleagues have embarked on a series of studies to better understand people’s individual preferences for their environments and they are doing it with QS tools. The first study was fairly simple. They tracked the ambient temperature and air quality of the person’s surroundings and used an app for feedback on whether the environment was “acceptable” or not. Carbon dioxide and temperature measurements were taken throughout the day, while the person was in the car, at work, the restaurant, etc.

4_Stefano Schiavon Personal Comfort Quantified Self MeetUp.007
Stefano and his colleagues noticed a couple things. One is that there was higher exposure to CO2 in air conditioned rooms as opposed to naturally ventilated rooms. While Stefano says that this CO2 level is not a concern in of itself, it correlates with other pollutants, such as, airborne transmitted diseases (e.g., influenza).

4_Stefano Schiavon Personal Comfort Quantified Self MeetUp.008

Despite these data, Stefano and his colleagues found that just recording the environment gave him a limited ability to predict a person’s comfort. He is hoping, and the focus of his next study, is that by getting a person’s QS data (heart rate and body temperature), this predication ability will improve, making it easier to personalize a space’s comfort for each individual.

4_Stefano Schiavon Personal Comfort Quantified Self MeetUp.010For Stefano, all of this is in support of a larger cause, climate change. He was saddened to discover that nearly 40% of greenhouse emissions come from buildings. He hopes that by building better models for personal comfort by using QS tools, he can help people enjoy their environments more, while minimizing the environmental impact.

You can see the entire video of his talk at his QS project page.

Here are links to some of Stefano’s papers:

Get your tickets for QS17

Our next conference is June 17-18 in lovely Amsterdam. It’s a perfect event for seeing the latest self-experiments, debating the most interesting topics in personal data, and meeting the most fascinating people in the Quantified Self community. There are only a few early-bird discount tickets left. We can’t wait to see you there.

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College Performance by Tiffany Qi


Tiffany’s calendar

I think I spent more time flailing than planning in college. Though I’m not sure, because I don’t have the data. Tiffany Qi does, though. During her four years of undergrad, she meticulously tracked her time, putting it in one of several categories, “planning” being one of them. Now that she has her degree in Business Administration, she spent some time analyzing the wealth of data she collected as an undergrad. For this talk, given at the a Quantified Self meetup last month in Berkeley, California, she focused on the relationship (or lack thereof) between how she spent her time and her academic performance.

In particular, she explored the following questions:

  • Did her commitment to her studies wane over time?
  • How much did time spent studying matter for her final grade?
  • Did the amount of time spent on fun help or hinder her grades?
  • Did having a job or other job-like responsibilities lower her grades?

You can watch the full video at Tiffany’s QS project page. For a more detailed look at this project, Tiffany wrote about it here and here.

Tools used:
-Google Calendar
-CalenTools (Tiffany’s custom tool that she made for this project)

Get your tickets for QS17

Our next conference is June 17-18 in lovely Amsterdam. It’s a perfect event for seeing the latest self-experiments, debating the most interesting topics in personal data, and meeting the most fascinating people in the Quantified Self community. There are only a few early-bird discount tickets left. We can’t wait to see you there.

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What We Are Reading

Even though our work at Quantified Self is not ostensibly political, we have been thinking lately about its relevance to the tumultuous times in U.S. politics. Although there is uncertainty and fear, we, like many others, feel activated to make a difference as individuals, more than we did before.

One of my fundamental beliefs about Quantified Self practices is that it leads people to be better versions of themselves. I don’t mean this in the bigger, stronger, or faster sense. It helps people become active agents in their lives. To be more curious and challenge certainty in themselves and others. In navigating this uncertain time and figuring out how to make a personal contribution, communities will play a larger role in people’s lives. It’s important to me, at least, that we are a community that encourages thoughtfulness and thoroughness in reasoning and perspective. I don’t know exactly what our role will be, but we stand in solidarity with those who fight for a better world and defend against capriciousness, avarice, and false confidence. In that spirit, my colleague Erica has put together a beautiful, short video of her experience at the Women’s March on D.C.

I hope you enjoy these articles. Some are a welcome respite. Others may help with understanding the current situation. If you have any suggestions for what we can do to help or if you read anything that we should include in a future WWAR, send it my way at



Algorithmic Life by Massimo Mazzotti. Trendy words become objects of derision. When a word with a range of meanings is overused, it becomes ever more ambiguous, as each discrepant situation through which it passes rubs away some of its precision, until the sound of the word does nothing more than evoke vague memories of where it’s been. Words that have been with us through many struggles, like “justice” or “pride,” acquire the opacity of nearly universal significance. But new minted words, without historical weight— people may just start to laugh them. The word algorithm has begun to suffer this fate. This sensitive essay by historian of science Massimo Mazzotti argues that the semantic confusion of “algorithm” is an invitation to revise our assumptions about people and machines. -Gary

Why Medical Advice Seems to Change So Frequently by Aaron E. Carroll. Nutritional recommendations are a tricky business. Some wonder why scientists can’t get their story straight. Sometimes the issue is that a perceived effect disappears when a more rigorous experiment is done. Another issue is that some people will benefit from an intervention, but it is then proclaimed that all people will benefit. There’s also the problem of studies with negative results being hidden from view. -Steven

Tracking Physiomes and Activity Using Wearable Biosensors Reveals Useful Health-Related Information, by Xiao Li, Jessilyn Dunn, and Denis Salins. This article from PLOS-Bio is a top contender for “QS Paper of the Year.” True, this award was just invented, and the year has barely started. Still, I invite you to download it and see if you can find reasons to disagree. Based on nearly two years of extremely detailed self-tracking by one 58-year old participant, and strengthened by additional group research, the paper makes substantive new discoveries and demonstrates the power of accessible tools for self-measurement. The participant is Mike Snyder, principle investigator in the Stanford lab where the authors work. (Aside from many other interesting things about the paper, it’s an important example of participatory research methods.) Back in 2011, an individual self-experimenter, John de Souza, gave a talk at our QS conference showing that he could predict sickness – before symptoms were felt – by looking at elevation of peak heart rate during exercise over a well established baseline average. Li, Dunn, and Salins’ paper contains a similar result based on elevation of resting heart rate. The data supporting this conclusion is very rich, including both self-reported symptoms and elevated hs-CRP, a marker of inflamation. There is much too much additional interesting material to quickly summarize; thankfully, PLOS-Bio is open access, so have at it. -Gary

Most People Are Bad at Arguing. These 2 Techniques Will Make You Better by Brian Resnick. Something that I see play out on Facebook currently is the futility of arguing with those that we disagree with. It’s not often the case that this does anything to change minds. This article looks at how empathy and listening can make a difference. -Steven

Cortisol and Politics: Variance in Voting Behavior is Predicted by Baseline Cortisol Levels, by Jeffrey A. French, et al. While I don’t have super high confidence the conclusions from this paper published in 2014 are going to hold up, the connection between variations in stress tolerance and participation in politics is very interesting, and more accessible measurement tools are going to allow a much closer look than we’ve ever had before. An intuitive understanding of how to induce and relieve stress has been part of politician’s toolkit forever, but now more than ever we need some kind of self-understanding of our own physiological patterns of response, in order to be able to reflect better on what’s happening around us. -Gary

The FDA Is Cracking Down On Rogue Genetic Engineers. Up until this point DIY biohacking has largely operated without government oversight. As this technology moves out of niche communities and becomes commercialized, there are concerns over whether the FDA will include DIY biology enthusiasts in the rulemaking process. -Steven

Show & Tell

The Year 2016 by Lillian Karabaic. Lillian releases her 9th annual report, with entertaining visualizations, whimsical metrics (e.g., tacos consumed), and a light-hearted, but not to be taken lightly, study of burnout from a new job. -Steven

Introducing BobAPI — A Personal API to Collect and Share All of My Life Data by Bob Troia. I missed this when he originally released it, but Bob created a unified data store that allows him to have control and ownership of his data and better equip himself to contribute to citizen science. I hope this proves to be a model that others follow. – Steven

A College Student’s Individual Analysis of Productivity of Four Years by Tiffany Qi. Tiffany recently graduated from UC Berkeley. During her four years of undergrad study, she tracked her time and productivity. In this analysis, she looks at how how her time spent affected her grades. -Steven

Data Visualizations


One Angry Bird: Emotional Arcs of the past Ten U.S. Presidential Inaugural Addresses. This analysis looks at facial expressions used by the last ten presidents as they give their inaugural addresses. Both the visualizations and method of analysis are novel. -Steven Often Do I Look at the Time? by Ravi Mistry. This is a of a visualization of a novel metric: “how often one looks at the time.” I’m impressed by the discipline required to pull this off. -Steven


AccidentalArt (1)Accidental aRt. This is a twitter feed for R visualizations that go “beautifully wrong.” My personal title for this beautiful work of accidental art is: “Causation is not correlation.” -Gary

QS17 Conference

QS17SidebarLogoOur next conference is June 17-18 in lovely Amsterdam. It’s a perfect event for seeing the latest self-experiments, debating the most interesting topics in personal data, and meeting the most fascinating people in the Quantified Self community. There are only a few early-bird discount tickets left. We can’t wait to see you there.

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Meetups This Week in Switzerland and Ireland

It’s 2017 and we’re looking forward to a new year of fun and informative Quantified Self meetups. This week brings the first of the bunch with Zürich and Dublin.  Zürich‘s meeting will feature a presentation on the current and future impact of the Quantified Self movement on Swiss society. Dublin will feature great talks on how to use blood testing to track and improve various biomarkers.

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! If you are a QS Organizer and want some ideas for your next meetup, check out the myriad of meetup formats that other QS organizers are using here.

Tuesday, January 10
Zürich, Switzerland

Friday, January 13
Dublin, Ireland

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What We Are Reading

It’s a new year, and we are starting it off with a collection of articles that we’ve been collecting for the last couple of months. I hope you find them as interesting as we did. -Steven


Making Statistics Matter: Using Self-data to Improve Statistics Learning by Jeffrey L. Thayne. Can Quantified Self projects solve an ongoing problem in teaching statistics? This doctoral dissertation supervised by Victor Lee, a long time participant in our Quantified Self Public Health symposia, argues that it can. The reason QS can help is simple: in QS practices, statistics become personally relevant. As Thayne writes:

[A]n essential feature of effective statistics instruction [is] a relevant, immediately available context of application, wherein learners feel that they are taking part in an ongoing inquiry process in which statistics is being used as a tool for illuminating something new and important about their world.

What I found especially interesting about this research, which used qualitative methods to explore student’s interest and involvement in their statistics learning, was that the use of self-collected data was not powerful because it appealed to the student’s vanity, but because it was familiar and had contextual meaning. Just as professionals who use statistical methods benefit from understanding where the data comes from and what it is for, students who can situate their practice in a rich context find it easier to master new methods. -Gary

On Progress and Historical Change by Ada Palmer. Historian and science fiction author Ada Palmer’s lucid essay on the idea of historical progress is great to read in light of the never-dying hope among the makers of self-tracking tools that there can be a formula for positive change. I sometimes tire out my colleagues opposing this idea, and I know it seems odd that here at Quantified Self we spend every day supporting people trying to figure out how to use technology for change while at the same time not believing that definite techniques for inducing such change can exist. Isn’t that a contradiction? In contrast to my usual philosophical abstractions and pedantic references to the history of behavioral psychology, Palmer tells the story of where our idea of progress comes from, and offers a fascinating account of how events can be simultaneously free and determined, based on the DIY historical simulation machine she builds every year with her students. -Gary

How a Guy From A Montana Trailer Park Overturned 150 Years of Biology by Ed Yong. One of my favorite stories in citizen science is how Beatrix Potter (of Peter Rabbit fame) was an early and ridiculed proponent of the idea that lichen was a symbiotic fusion of a fungi and an algae. The need for the term “symbiosis” arose from this discovery (credited to Swiss botanist Simon Schwendener). This article follows the humble beginnings of Toby Spribille and the process for how he determined that the theory that lichen is composed of two organisms is wrong. It’s actually three. -Steven

How To Do What You Want: Akrasia and Self-Binding by Daniel Reeves. I’ve been going back and reading some of Daniel Reeves’ excellent posts on the Beeminder Blog about the cluster of concepts and techniques associated with self-control, including also Smoking Sticks and Carrots and What is Willpower? -Gary

How Language Helps Erase the Tragedy of Millions of Road Deaths by Julie Sedivy. What is the difference between the words “accident” and “collision”? The word “accident” implies a lack of blame. This article explores the effects that these connotations have on our subconscious interpretation of the world. -Steven

Faster, Not Smarter: Does Caffeine Really Make You More Productive? by Alex Senemar. Alex surveys what is known about the effects of caffeine on productivity. How do you keep caffeine a boon and not a crutch. What I love about this article is that Alex finishes it with suggestions on how to run your own experiment to see caffeine’s effect on your productivity. -Steven

In Defense of Tracking Our Poop by Adam Butler. Adam makes the argument that one of the best ways to understand the health of the microbiome is to track and pay attention to your poop. How do you turn that into data? Luckily, there is a time-tested classification system that your physician should recognize called the Bristol Stool Scale. Which will help the next time you need to talk to your doctor. -Steven (courtesy of Ernesto Ramirez)

Childhood trauma leads to lifelong chronic illness — so why isn’t the medical community helping patients? by Donna Jackson Nakazawa. “Were there any childhood traumas or stressors that might have contributed to the extreme level of inflammation you’re experiencing as an adult?” Nakazawa says that this was the most important question posed to her in her adult life. From the question, she was able to untangle how her present day health issues have ties to the traumatic death of her father when she was twelve. The article shows that childhood trauma leads to a great likelihood of autoimmune disease. However, knowing about these links, one can help reduce the number of doctor visits. -Steven

Early Modern Bookkeeping and Life-Writing Revisited: Accounting for Richard Stonley, by Jason Scott-Warren. The use of numbers as an element in personal record keeping is ancient, but the account books of early modern elites hold particular interest for historians, since they seem to hold clues to the origin of today’s autobiographical habits. The great 17th century diarist Samuel Pepys kept his entries in a ledger book, and the carefully folded pages and ruled lines of the account books of bourgeois merchants and lawyers provide a dense cultural background for more famous documents (such as Benjamin Franklin’s memoirs) commonly imagined to to lie at the root of the Quantified Self. This essay from The Social History of the Archive (a special volume of the journal Past & Present) takes a close look at the account book of an obscure functionary named Richard Stonley, and shows how mistakes, repetitions, and elisions challenge the idea of the ledger book as a crucible for the modern sense of self. -Gary


How Software, Data, and a Hell of a Lot of Work Helped Me Lose 110 pounds in 25 Months by Timothy Chambers. Although he doesn’t show his data, it was interesting to read how Timothy integrated various tools into his effort to lose weight. Each tool had a role and each needed certain features to qualify. It’s a complex interaction of data sets and feedback mechanisms. I appreciated one of his points on data portability:

It was critical that my apps could speak to each other and to the cloud, not just to what companies each toolmaker had deals with. My web-based trend tools needed to talk with my scale which needed to speak to my phone. We work so hard for the health data about steps, weight, fat percentage, etc, that should be our data open to use with whatever tools we wish. Not all vendors treat it as such.


My to-do list is now public, and it’s the most useful thing I’ve done in years by Joe Reddington. For years, Joe has kept track his number of open to-do’s. In May, he experimented with making his to-do list publicly available. Now that he knows that he’s being “watched”, he is more conscientious about making his items comprehensible, and is  more motivated. As Joe puts it: “When it was [just] a list for me, it looked great; when I decided to make it public, it instantly looked very poor.” -Steven

Analysis of a Personal Public Talk by Alex Martinelli. Alex analyzes a recent talk he gave at a QS Dublin meetup, by looking at his heart rate and speaking speed. The piece has an appropriately casual tone, but he finishes each section of the analysis with a definitive statement based on the data. After looking at how fast he was talking, Alex writes as if he was consulting someone else:

Your average speech rate is 152 Words Per Minute (WPM), but an approximately constant and significant decrease can be observed, bringing you from an initial WPM of 166 to a final value of 142. The primary cause of this is the usage of increasingly longer pauses between words, secondarily reinforced by a combination of using longer words, as well as a tendency to slow down the pronunciation of words, while the talk unfolds.”

As an engineer at IBM, he’s clearly used to this at his job, but I like the idea of bringing this structure and formality to personal data analysis. -Steven

The Somniloquist by Adam Rosenberg. Adam was told by others that he talks in his sleep, so he set up a recorder to capture his “midnight monologues”. The recordings are transcribed, and in addition to being hilarious, they are an interesting insight into what the brain is doing during sleep. -Steven

My Quantified Wardrobe 2017 by Matt Manhattan. Matt analyzes his wardrobe in an effort to define his relationship with his clothes. He looks at how much of each article of clothing he has and their associated cost. But it’s the pictures of his clothes that makes this post delightful. -Steven

Data Visualizations

History Lesson by Clive Thompson. Not a visualization, but an article about the history of data visualizations. -Steven

The London Wind Map. A whimsical of visualization of where you would go if “you were pushed by the wind each day” in 2015. -Steven


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Ahnjili Zhuparris: Menstrual Cycles, 50 Cent, and Right Swipes


“I love reading random papers about the human body.”

Ahnjili Zhuparris came across a study on the menstrual cycle’s influence on cognition and emotion and was curious to see how hormonal changes may affect her day-to-day behavior. She figured her internet use may be a convenient and easy data set to assemble and examine for this effect. Using a few chrome plugins, Ahnjili was able to see not only where she spent her time online, but how she interacted with sites like Facebook and Youtube.

Her analysis yielded some interesting patterns. She found the most distinctive behaviors occurred during the fertile window, a span of about six days in the menstrual cycle when the body is most ready for conception. Looking at her shopping data from a clothing website:

 ”I found that there was no change in the amount of money I spent or the amount of time I shopped online… but while I was most fertile, I bought more red items. In fact, it was the only time I bought red items.”

In this talk, Ahnjili shows the differences in how she browsed Facebook, swiped in Tinder, and listened to music on YouTube.

Here are a few of the tools and papers that Ahnjili cites in her talk:

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