2015 QS Visualization Gallery: Round 4

We’re excited to share another round of personal data visualizations from our QS community. Below you’ll find another five visualizations of different types of personal data. Make sure to check out Part 1Part 2, and Part 3 as well!

daily habits Name: Damien Catani
Description: This is an overview of how I have been doing today against my daily habit targets. Yes, I had a good sleep!
Tools: I used a website I’ve been building for the purpose of setting and tracking all goals in life: goalmap.com

 

tock_b_tock_goal_page Name: Bethany Soule
Description: This is my pomodoro graph. I average four 45 minute pomodoros per day on my work, and I track them here. This is where most of my productivity occurs! There’s some give and take.
Tools: The graph is generated by Beeminder. I use a script I wrote to time my pomodoros and submit them to Beeminder when I complete them. The script also announces them in our developer chat room, so there’s also some public accountability there as well.

 

 

qs1 Name: Steven Zhang
Description: This plot shows the time I first go to sleep, against quality of day (a subjective metric I plot at the end of every day). What this tells me is that if I get a full night’s sleep of 8 hours, for every hour I got to bed, I can expect a .16 decrease in my QoD rating, which, given my range of QoD around 2 to 4, is about a 5% decrease in quality of day.
Tools: Sleep as Android to track sleep and some python scripts for ETL.

 

qs2Name:Steven Zhang
Description: Log of all my sleep for the last 6 months, labeled by the types of sleep I most often encounter

  1.  Normal sleep
  2. Napping
  3. 3. Trying to achieve normal sleep, but failing to

Tools: Tableau for visualization. Sleep as Android for logging sleep.

 

Digits
Name: Eric Jain
Description: Benford’s Law states that the most significant digits of numbers tend to follow a specific distribution, with “1″ being the most common digit, followed by “2″ etc. But my daily step counts show a slightly different distribution: The fall-off from “1″ to “2″ is larger than expected, and the frequency of digits larger than “5″ increases rather than decreases. Is this pattern typical for step counts? Could suspicious distributions be used to detect cheaters?
Tools: Fitbit, Zenobase, Tableau

Stay tuned here for more QS Gallery visualizations in the coming weeks. If you’ve learned something that you are willing to share from seeing your own data in a chart or a graph, please send it along. We’d love to see more!

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QS15: A Review

QS15 Tweet Robot designed by The Living. Photo: Rajiv Mehta

QS15 Tweet Robot designed by The Living. Photo: Rajiv Mehta

In just little more than a month we’ll be convening in lovely Amsterdam for our 2015 Quantified Self Europe Conference. While some might call us crazy since we just wrapped on our big QS15 Conference in San Francisco, we like to think that we’re on a tour, inviting people from around to world to engage and learn about the power of personal data.

With QSEU15 so close, we decided to take a quick look back at what makes our conferences so special. Rather than telling you what we think we thought it would be best to highlight the thoughts and writing from individuals who attended and participated in our 2015 Quantified Self Conference. We’ve gathered up links to articles, blog posts, and write-ups of all types and are posting them here for you to read and review.

If you’re intrigued by the ideas and events described in the links below make sure to register for QSEU15. Early Bird tickets are on sale for just a bit longer so take advantage now!

Training the Next Generation of ‘Quantified Nurses’

Quantified Self ’15 (Day 1 Recap)

Quantified Self ’15 (Day 2 Recap)

What’s a Self Anyway?

Compass Alpha at the Quantified Self Conference 2015!

Quantified Self Expo, Part I

Quantified Self Expo, Part II 

About the Quantified Self Conference and Expo

Own your Biological Machine

Quantified Self 2015

Architecting health data for the cloud

What you can learn from the 2015 Quantified-Self conference

QS15: Measurement with Meaning

More About Me at QS15

What I learned at Quantified Self 2015

Notes from the 2015 Quantified Self Conference

My Data, Your Data, Our Data

News from the Quantified Self movement

Quantified Self Labs

Some of the Best from the 2015 Quantified Self Conference

Personal Gold @ Quantified Self ’15

Learning about new self-tracking technology at QS15

If you wrote something about your experience at QS15 let us know! We’d love to feature it.

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Meetups This Week

There will be three Quantified Self meetups this week. Zürich will have a toolmaker talk from Boonea on taking a quantified approach to relationships and personal networks.

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, August 11
Lansing, Michigan
Zürich, Switzerland

Saturday, August 15
Denton, Texas

Meetups Last Week
Here are some images from Berlin‘s great meetup last week. If you organize a QS meetup, please post pictures of your event to the Meetup website. We love seeing them.

600_440630891 600_440630887 600_440630890 600_440630897 600_440630896
photos courtesy of Johannes Breyer

 

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What We Are Reading

We’re back again with another round of What We’re Reading. Before diving into the great articles and links below why not take some time to subscribe to our QS Radio podcast! We just released our fourth episode and would love to know what you think!

Want to tell us in person? Why not join us for our fourth QS Europe Conference this September in Amsterdam! Register now to take advantage of our early bird pricing.

Articles
Got Sleep Problems? Try Tracking Your Rest with Radar. by Rachel Metz. Researchers at Cornell University, the University of Washington and Michigan state are conducting research using off the shelf components to see if non-contact sleep tracking is possible. Turns out it is!

Apple’s Fitness Guru Opens Up About the Watch by Scott Rosenfield. A nice interview with Jay Blahnik here, where he speaks to Apple’s focus on self-tracking and fitness with the Apple Watch.

To share is human by Laura DeFrancesco. In this great news feature, Laura DeFrancesco exposes some of the issues with sharing personal data, as well as the initiatives hoping to break through those issues to help bring more data into the public sphere.

Using Twitter data to study the world’s health by Elaine Reddy. A great post here profiling John Brownstein and his work in Computational Epidemiology, specifically how he and his research team use public data sources like Twitter to tease out signals for health research.

Show&Tell

Charts.001 Comparing Step Counts: Apple Watch, Fitbit Charge HR, And IOS Withings App by Victor Lee. An awesome and in-depth post comparing almost two months of steps counts from three different tracking methods by our friend Victor Lee. Glad to see he put our QS Access app to good use!

Follow-up to how I lost over 40 pounds using HealthKit and Apple Watch by Jim Dalrymple. Jim tells his story of how using a variety of apps and tools, all linked to his Apple Healthkit app, helped him learn about himself and eventually put him on the path to sustained weight loss.

Tracking Confidence by Buster Benson. Buster always has something interesting to say about self-tracking. This time is no different. Here he briefly talks about asking himself, “how confident do I feel right now?”

Visualizations


The Heart Chamber Orchestra.

The Heart Chamber Orchestra – HCO – is an audiovisual performance. The orchestra consists of 12 classical musicians and the artist duo TERMINALBEACH. Using their heartbeats, the musicians control a computer composition and visualization environment. The musical score is generated in real time by the heartbeats of the musicians. They read and play this score from a computer screen placed in front of them.

From the Forum
How to acquire info about sent e-mails using gmail?
Looking for Android exercise tracking app
Resting Heart Rate tracking

This Week on QuantifiedSelf.com
QS Radio: Episode #4

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QS Radio: Episode #4

QSradio_iTunes

We’re back with another episode of QS Radio! In our fourth episode we learn a bit about Steven Jonas, and the many different trackers he’s using and then it’s on to a great show&tell interview g with Mark Leavitt, co-organizer of the Portland QS meetup group about his experience with measuring HRV and it’s effect on his willpower. We wrap up as usual with a short discussion on things we’re finding interesting out there in the QS world. Click the links below to listen and/or subscribe and follow along with our show notes.

Download the episode here or subscribe on iTunes.

Links:

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Meetups This Week

Five Quantified Self meetups are getting together this week. Manchester will be talking about data dashboards and Berlin has a great slate of talks on blood glucose tracking, transitioning to a Colemak keyboard layout, and how to look for signals from one’s body.

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.

Monday, August 3
Manchester, England
Oxford, England

Tuesday, August 4
Reno, Nevada

Thursday, August 6
New York City, New York
Berlin, Germany

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What We Are Reading

A long list for this week’s What We’re Reading. I actually had to stop myself from adding in even more visualizations and show&tell examples! We’re always on the lookout for more though, so make sure tweet us your favorite links!

Articles
Fitted by Moira Weigel. A very thoughtful essay on gender, identity, and confession – all while using the Fitbit as the narrative backdrop.

What kind of love does the FitBit prepare us to feel? Is it self-love? Or is even the self of the exorexic a kind of body armor?

How to Build a Smart Home Sensor by Dave Prochnow. If you have 2 hours, $95, and know how to solder, then you too can build this DIY sensor to measure the temperature, humidity, light, and noise for any room in your home. If someone builds and tests this please let me know (Would love to see air quality sensors included too!)

It’s Hard to Count Calories, Even for Researchers by Margot Sanger-Katz. New research shows Americans are eating less, but can we really trust the data? Margot does an excellent job here of rounding up the various ways we measure food consumption in the United States while coming to a commonly heard conclusion – food tracking is just plain hard.

Hadley Wickham, the Man Who Revolutionized R by Dan Kopf. If you’re knee deep in data analysis, or just like poking around in stats software, you’ve probably heard of and used R. And if you’ve used R, then there is a good chance you’ve used many of the packages written by Hadley Wickham. Great read, if for nothing else you learn what the “gg” in ggplot2 stands for.

Heart patient: Apple Watch got me in and out of hospital fast by Neil Versel. When Ken Robson wasn’t feeling well he turned to his Apple Watch. After noticing lower than normal heart rate readings his checked himself into the emergency room and soon found out his hunch was right, he had sick sinus syndrome.

New Australian experiment rewards joggers with 3D printed chocolate treats based on exercise data by Simon Cosimo. Sign me up!

Show&Tell

Screen_Shot_2015-07-24_at_11.41.15_AMHow Does Giving Blood Affect Your Iron Levels? by Ryan W. Cohen. Simple and to the point blog post by Ryan explaining how he discovered elevated iron levels in his blood, and the simple test he tried to find out why.

The Quantified Athlete by Matt Paré. Matt is a minor league catcher in the San Francisco Giants organization. In this post, the second in a series (read Part 1 here), Matt discusses how he became interested in tracking his biomarkers, and what he’s experimenting with.

What I Learned When I Stopped Wearing a Fitbit After Seven Years by Michael Wood. Michael writes up a brief post on how he felt when he was separated from his Fitbit activity tracker.

1*n0JEGs6Mzgiri0kAUYPDkgHow I tracked my house movements using iBeacons by Joe Johnston. Joe uses a few iBeacons to find out where he spend time in his house. Fascinating idea, makes me want to play with this technology as well!

Visualizations

Screen Shot 2015-06-30 at 8.55.26 amVisualizing a Simpler RunKeeper Training Plan by Andy Kriebel. Andy presented his running data, and how he uses a few tools to keep track and visualize his data as he trains for a marathon. Follow the link and you can see his Tableu workbook, which includes a screencast of his presentation, and links to his workflow.

gIV8BlGI decided to take a peek at my Netflix viewing data by Reddit user AmericanPicker69. This enterprising individual decided to take a peak into his user account to understand his Netflix viewing habits. Turns our a simple copy/past is all you need to do to get the raw data. Who knew?!

eUKFHBOMy weight loss journey by Reddit user IMovedYourCheese. Loved this graph and the implementation of BMI categories, a moving average, and lower/upper bounds for weight loss. He even provided the excel template if you’d like to use it with your own weight tracking.

From the Forum
Teach Arduino from Beginner to Making a Quantified Monitor
Google Fit

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Why Quantified Self Show&Talks are Amazing

I have had the esteemed pleasure for the last couple of years of helping speakers at Quantified Self conferences put together their talks. It’s a lot of work for me, but more so for the speakers. At the QS15 Conference last month in San Francisco, I took the opportunity to not only express my appreciation for our speakers’ effort, but to also speak to why the act of sharing your own personal data experience is so important and has historical precedent.

Below is a video of the speech along with the prepared remarks:

My role at the conference is to help our speakers put together their show&tell talks. For every speaker, we have a forty-five minute discussion to go over their talk.

It’s a role I relish because I get to see the process that people go through to turn their personal experience into the form of 30 slides in 7 and a half minutes.

Unless you’ve given a show&tell talk, it’s hard to know the effort and difficulty inherent in presenting one’s story. There’s the doubt and questioning of why anyone would be interested in my personal experience. How do you decide what is the right amount of context to give people? How do you sequence the information so it is intelligible?

But if I may, I want to spend a moment to talk about this practice of self-examination, and why I think it is so special.

Something that came to mind while mulling this over is something Sarah Bakewell wrote in a book about Michel de Montaigne, the 16th century french philosopher.

“Montaigne and Shakespeare have each been held up as the first truly modern writers, capturing that distinctive modern sense of being unsure where you belong, who you are, and what you are expected to do.”

If you don’t know, Montaigne was famous for a series of philosophical essays written in the 1500’s.

What was special about his essays was how honest and self-reflective he was, if meandering and digressive. But this style was novel at the time. Montaigne’s philosophical inquiries were not expansive and universal. They were small. They were constrained to just himself.

What’s funny is that this sharing of one person’s self-examination was wildly popular. For next few centuries every generation saw itself in Montaigne. Picking out different aspects of him that resonate.

By limiting the scope of conveying an experience, the power to resonate with people is much stronger and wider than it would be if you strove to be universal.

What makes Show&Tells special is that they are personal. They are small, honest, and vulnerable. They are from individuals who are humbly trying to figure out who they are and what they should be doing.

I think we are all blessed by their graciousness and generosity in sharing their experiences, so that we can see ourselves in them and figure out how to navigate our own place in a huge, immensely interesting but very confounding world.

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2015 QS Visualization Gallery: Part 3

We’re excited to share another round of personal data visualizations from our QS community. Below you’ll find another five visualizations of different types of personal data. Make sure to check out Part 1 and Part 2 as well!

eddie-flights Name: Edward Dench
Description: All recorded flights I’ve taken.
Tools: Manual entry into openflights.org (there is an interface using TripIt though).

 

QS Visualization Name: Siva Raj
Description: After 6 months of regular exercise failed to improve my fitness and blood pressure levels, I switched to training above my endurance limit (anaerobic threshold). This was higher intensity but half the cycling time, yet my fitness and blood pressure improved within weeks.
Tools:Revvo – tracking fitness and intensity of workout; Withings – weight; iHealth BP Monitor – BP. Visualization created by overlaying Revvo screenshot with other information in photoshop.

 

Screenshot 2015-06-05 08.07.14 Name: Kurt Spindler
Description: Grafana is a common tool in the Software community to create beautiful dashboards to visualize server health (network, requests, workers, cpu, etc.) and therefore more easily diagnose problems. I created a custom iOS app that allows me to publish metrics to the same backend as Grafana, giving me Grafana dashboards for my personal health.
Tools:Custom iOS app, Grafana, Graphite
RyanODonnell_PagesReadPerMonthName: Ryan O’Donnell
Description: This semi-logarithmic graph is called the Standard Celeration Chart (SCC). It’s beauty is that anything a human does can be placed on this chart (i.e., standardized display). This also allows for cool metrics to be developed that lend well to predictability. I charted the number of pages that I read for my field of study, Behavior Analysis. I wrote a blog post on the display to speak some to the reading requirements suggested by professionals in the field. There were many variables that led to variations in reading rate, but the point of this work was to try and establish a steady reading repertoire. A recent probe in May of 2015 was at 2800 pages read. Essentially, I learned how to incorporate reading behavior analytic material almost daily in my life, which indirectly aids in the effectiveness I have as a practitioner and supervisor.
Tools: Standard Celeration Chart and paper-based data collection system (pages read each day on a sheet of paper).

 

Graph4_red_black Name: Francois-Joseph Lapointe
Description: This *Microbial Selfie* depicts the gene similarity network among various families of bacteria sampled from my gut microbiome (red) and oral microbiome (black). Two bacteria are connected in the network when their gene sequences are more similar than a fixed threshold (80%). The different clusters thus identify bacterial families restricted to a single body site (red or black) versus those inhabiting multiple body sites (red and black).
Tools: In order to generate this data visualization, samples of my oral and gut microbiome have been sequenced on a MiSeq platform by means of 16S rRNA targeted amplicon sequencing, and the resulting data have been analyzed using QIIME, an open-source bioinformatics pipeline for performing microbiome analysis. The gene similarity network was produced with the open graph viz platform Gephi, using the Fruchterman–Reingold algorithm.

Stay tuned here for more QS Gallery visualizations in the coming weeks. If you’ve learned something that you are willing to share from seeing your own data in a chart or a graph, please send it along. We’d love to see more!

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Damien Catani: Tracking 7,459 Dreams

DamienCatani_Dreams

After going through a life crisis during his teenage years, Damien Catani turned to tracking his dreams to help “rebuild his sense of self.” Eighteen years and seven thousand dreams later Damien shared his tracking process and what he’s been learning at the QS15 Conference and Expo. In his data he found patterns for the number of dreams he experienced and remembered according to the day of the week, season of the year, and the affect of different lifestyle factors.

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