Topic Archives: Conference

Maggie Delano: Building Myself Back Up

Maggie Delano hit her head while helping a friend move. She was diagnosed with a concussion and, later, post-concussion syndrome. In order for her to heal, she had to give her brain a break from cognitively stimulating activities. In this show&tell talk, presented at the 2015 Quantified Self Conference, Maggie discusses how she tracked her progress toward recovery with Habit RPG (recently renamed Habitica) and improved her sleep with Sleepio.

To see great presentations like Maggie’s in person and get the chance to talk with the speakers, come to our Quantified Self Europe Conference on September 18 & 19. Our early-bird tickets (€149) expire in less than 24 hours, so get yours now!

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QSEU15 Preview: Morris Villarroel on Slowing Time with a Lifelog

Morris Villarroel at QS14

The 2015 Quantified Self Europe Conference will commence in less than four weeks, bringing together the QS community to share what they’ve been learning with personal data.

Anyone who engages in any sort of self-tracking discovers that the data collected is not a mere recording of some aspect of your life. Rather, engaging with and reflecting on that data can change the way that you relate to an aspect of yourself. Something as simple as getting on a scale each morning can change the way you think about weight. Morris Villarroel has discovered a novel way that this relationship can develop. At this year’s conference, Morris will talk about how using a Narrative camera to keep a visual record of his days, along with detailed notes, has changed his subjective experience of time, “bringing it closer to the present.”

I experienced something similar when I used a spaced repetition system to memorize entries from my daybook. Frequently recalling recent events kept the past distinct and novel. When a month passed, it no longer seemed like a blur, but a container filled with distinct experiences that differentiated itself from any other month.

You can find out more about how Morris gleans value from his lifelog at the 2015 QS Europe Conference. In addition to his show&tell talk, Morris will be leading a breakout discussion on how we can learn more from our lifelogs. We invite you to join us in Amsterdam on September 18th & 19th for two full days of talks, breakout discussions, and working sessions! Early bird tickets are still on sale. Register today for only €149!

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QSEU15 Preview: Ellis Bartholomeus on Doodling Mood

EllisMoodFaces

In just four short weeks we’ll be kicking off the 2015 Quantified Self Europe Conference, and we are so excited to hear from old friends, learn from new members, and interact with some wonderful toolmakers. It’s going to be a great time.

As you may know, we build our conference programs from the ground up with attendees submitting their projects and ideas when they register. It’s always fun to read about someone’s new self-tracking project or experiment, especially when it involves something we haven’t seen before. Today we’re going to begin our conference previews with one of those novel and interesting talks.

EllisB

 

Ellis Bartholomeus is no stranger to our QS Conferences, having given an excellent talk on using photos for food tracking at our 2013 Europe Conference. At this year’s conference Ellis will be sharing her experience with a very interesting type of mood tracking. For six months Ellis tracked her mood by drawing a face every day. This simple act of using a quick doodle to track how she was feeling led to some unexpected benefits:

 

This inspired and engaged me more than expected with other quantifications. The faces triggered my curiosity and provided many insights, which continue to motivate me.

Mood tracking is something that continues to intrigue our community. Understanding our happiness, what affects our mental state, and how to improve our moods is a common theme at meetups around the world. We’re interested to learn more from Ellis and her experiences at the 2015 QS Europe Conference. If you’re tracking your mood we invite you to join us in Amsterdam on September 18th & 19th for two full days talks, breakout discussions, and working sessions! Early bird tickets are still on sale. Register today for only €149!

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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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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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QS Radio: Episode #3

QSradio_iTunes

After a bit of a hiatus, mostly due to our planning and production for the QS15 Conference and Expo, we’re back again with another episode of QS Radio. Join us as we discuss last month’s conference, including the great show&tell talks, breakout sessions, and some of the great exhibitors.

Download the episode here or subscribe on iTunes.

Links:
QS15 Photos
Whatify
Muse
Thync
The BrainStimulator
iBeacon

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2015 QS Visualization Gallery: Part 2

We’re back again with another round of visualizations from our QS15 Conference and Expo attendees. In today’s batch you’ll see a variety of representations of different tracking projects, from tracking biometrics while watching a movie to running distance over nearly 13 years. Enjoy!

interstellar-hr-hrv-gsr-1024x635 Name: Bob Troia
Description: I tracked my heart rate, HRV, and galvanic skin response while watching the movie Interstellar (in IMAX!), then plotted the data to understand how my body reacted during the 3+ hour movie. (Check Bob’s blog post about this data here!)
Tools: Polar H7 chest strap, SweeBeat Life app (iPhone), Basis B1 band, Excel.

 

Sleep for a week Name: Tahl Milburn
Description: This shows sleep over a week. The overall height of the bar is the time in bed. The part above the baseline is actual sleep whereas the part below 0 is restless sleep or awakening during the night. The line above the bars is the goal number of hours. The bar itself is green is all okay, turns yellow if overall duration is short or awakened too much. Red is even worse.
Tools: Google Charts with data from Fitbit.

 

LifeGauge Name: Tahl Milburn
Description: This is a very simple but powerful chart. T his is a “Life Gauge” which show how much of my statistical life has already been used. The ultimate age is based on the consensus estimate from several sources. Note the yellow and red markings indicating that one might be running out of life soon.
Tools: Google Charts for the graph itself. Several sources for computing the ultimate age.

 

BigGraph Name: Julie Price
Description: My running miles per week plus marathons since 2002.
Tools: Tracked running miles using various methods and recorded both on paper and, in the past few years, on a Google sheet. Summarized & graphed in Excel before manually adding in marathons.

 

IMG_8244 Name: Allan Caeg
Description: ”How much did you win today?” is one of the most important questions I ask myself every day. This pre-sleep question constantly gets me to reflect on what I did with my free will, inspiring me to ensure that I’d make the most out of every day.
Tools: Reporter

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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