Tag Archives: tableau
A man who tracked five years of sneezes might have a fix for your pollen allergy by Akshat Rathi. Thomas Blomseth Christiansen has spoken about tracking his sneezes at QS conferences. This article is a good telling of Thomas’s story.
Good tool with too small market can get a second chance – a hardware hack saves Zeo by Portabla Media. A short article on how Philipp Kalwies responded to the demise of Zeo. Since the sensors in the headband need to be replaced every three months and official supplies were dwindling on the secondary market, Philipp began to make his own and hopes to have this resource available to the small group of users who continue to get value from their Zeo devices.
The Right to Repair Ourselves by Kim Bellard. A common question in the QS community is “who owns your data?” Another question that should be given more time and is explored here, is “who owns the knowledge of how to ‘fix’ yourself?”
The Habits of Tracking My Diet and Exercise Data by Shannon Connors. Shannon has some of the most impressive personal data sets that I have ever seen. In this post, she gives an overview of the tools that she uses, what about the data she finds useful, and how she integrates the data collection into her day.
What you can learn from 2 years of Coach.me habit tracking + Machine Learning by Bryan Dickens. Applying association analysis to his coach.me data, Bryan was able to see which of his habits tended to occur together. There are some intriguing insights in here.
Visualizing Data in My Sleep with Tableau by Robert Rouse. Robert shows how his sleep patterns changed after the birth of his child.
At every conference, a synchronicity will occur where a few talks cover a similar, but previously unexplored topic. At QS15, we were surprised to see an increased discussion of concussions. It’s hard to know whether this is due to random chance or a glimmer of the zeitgeist, but we like to take note of these little waves of how people are finding new ways to understand themselves, or in this case, overcome strife.
Though Steven Zhang had a history of sleepiness and headaches, he never tracked them prior to his concussion. But during his recovery from post-concussion syndrome (which worsened his sleepiness and headaches), he wanted a clear record of his progress. He tracked headaches using the Tap Log android app and tracked his sleep using Sleep As Android, manually logging in and out in the app as he prepared for or woke from sleep. That he naps often and has many unsuccessful attempts to sleep meant that automatic methods for tracking sleep, like wrist-worn activity trackers, were ineffective, an important lesson considering that good sleep data is still sought after by many in the QS community.
Visualizing his data in Tableau, he gained a sense of norms for his headache frequency and nap lengths, allowing him to test the effectiveness of a dietary intervention, the fascinating result of which you can watch in the video of his talk below:
Steven presented this talk last month at the QS Global Conference in San Francisco. To see more great talks like this, you should join us at our Europe Conference on September 18 and 19th in Amsterdam. We have a limited number of early bird tickets available, so make sure that you don’t miss out by registering!
In 2009 Tim Ngwena switched on Last.fm and he’s been running in across all his devices ever since. Earlier this year he decided to take a deep dive into his listening data to see what he could learn.
I realized that I was listening to the same old thing and I began to think about changing what I was listening to. But how can I change? Where can I start? I also wanted to learn something about my music, what I was listening to and who was behind the sounds. I decided to focus on music because it was doable.
In this talk, presented at the London QS meetup group, Tim explains how he was able to make sense of almost five years of data and learn more about himself and his listening habits.
What Did Tim Do?
Tim explored his music data along side additional information such as location data from Moves to learn about his musical tastes, listening habits, and explore new visualization and data analysis techniques.
How Did He Do It?
Tim exported his data, used the Last.fm API and some data cleaning and organizational tools to create a simplified and extensive database of his music listening history and associated data. He then visualized that data using Tableau.
What Did He Learn?
Tim learned a lot about himself and what the music he listens to says about him. He describes a few of the most interesting below,
Basically 80% of my listening comes form 10% of the artists that I have in my library.
I’ve listened to Erykah Badu for over a week (7.2 days). It led me to ask what is she saying to me?
Monday is my jam time. I’m listening from the morning into the evening.
I listen to music mostly when I’m walking.
Tim also learned a lot through the process of designing and creating his data visualization. The visualization, which you can explore here, made him think about being able to see the big picture when he has so much linked data.
I think context is important and you need to see all that information in one place and the tools I’m using allows me to do this.
We’ve compiled quite the variety of articles and links for you. Make sure to check out the show&tell and visualization sections below for some great Quantified Self examples. Enjoy!
Articles & Posts
To lead off today’s list I’m including two great posts from attendees at our recent 2014 QS Europe Conference. You can read more attendee recaps over onour roundup post.
Ten Things I Learned at the 2014 Quantified Self Europe Conference by Bob Troia. Bob takes a look back at the conference and describes his experience.
Quantified Self and Philosophy at #QSEU14 by Kitty Ireland. We hosted over 36 breakout discussion at our recent European Conference. In this post, Kitty describes one of the “standout sessions” that she attended.
Okay, back to list!
Wearable Computers Will Transform Language by Ariel Bleicher. This is a long piece, full of excellent examples of how personal personal computing is becoming, but my favorite leads the article. Wearable computers in 1961. Who knew!
CyclePhilly hopes to record biking patterns to help plan bike lanes by Jim Smiley. A big theme of our discussions at various QS events this year has been around the social and public good the personal data can do. This project, led by Corey Acri and Code for Philly, hopes to better understand where commuters are actually riding their bikes. This also reminded me of a recent data sharing deal between Strava (a GPS activity tracking app) and the Oregon Department of Transportation.
How Much Can We Demand of Consumer Connected Health? by Joseph Kvedar. We’ve mentioned this before on both the QS blog and in the reading list, self-tracking device accuracy is a tricky concept. In this short post Dr. Kvedar describes his experiences and some results using consumer tools in a clinical setting.
In-Depth: How Patient Generated Health Data is Evolving Into one of Healthcare’s Biggest Trends by MobiHealthNews. This is a nice long piece covering many aspects of the growing role of different types of health data in healthcare. I personally enjoyed learning more about the challenge of combining patient reported data with electronic medical records.
Treadmill Effect of Spaced Repetition Performance by Gwern. In this exhaustive examination, our friend Gwern decided to test whether walking on a treadmill helped his memory. Specifically he randomized if practiced his spaced repetition while walking at his treadmill desk or sitting down and then looked at his grades (flashcards remembered correctly). You’ll have to read it to see what he foun. (Make sure to check out his other experiments as well!)
My Sleep Cycle Experiment and What to Limit Before Bed by Greg Blome. This is a great breakdown of what Greg found out about what affects his sleep by tracking 150 nights of sleep with the Sleep Cycle app.
Learning Ancient Egyptian in an Hour Per Week with Beeminder by Eric Kidd. Here at QS Labs we have a soft spot for spaced repetition (See Gary Wolf’s great primer here). This post details how Eric learned how to read Egyptian hieroglyphs using spaced repetition and Beeminder.
OpenVis Conference. Here you’ll find 18 great presentations by leading data visualization experts. Hard to pick a favorite, but I found Andy Kirks, The Design of Nothing: Null, Zero, Blank to be fascinating.
Breeze Habits by Runkeeper. The data science team at Runkeeper took a look at 75,000 worldwide Breeze App users to see what countries were getting up earlier, going to sleep later, and getting the most steps. I can’t wait to see more visualizations like this from Runkeeper.
Tableau Quantified Self Viz Contest. We mentioned this is last week’s reading list and the contest has is now over and we get to peruse the great entries. I’m going to include some of my favorites below, but make sure to check out all of them at the link above. You can also view the winners here.
The Life of Spangler by Russell Spangler. Russell tracked his time for the month of April and presents the results.
Runderground by Carl Allchin. Have you ever wondered if it’s faster to run than take the tube in London? Carl has your answer.
Beating Diabetes by Andre Argenton. Andre accessed the data in his Dexcom continuous glucose monitor and visualized it alongside data from his OmniPod insulin pump.
From The Forum
Measuring Cognitive Perormance
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