Tag Archives: visualization
We had a lot of fun putting together this week’s list. Enjoy!
A Spreadsheet Way of Knowledge by Steven Levy. A few weeks ago we noted that it was the 35th anniversary of the digital spreadsheet. Steven Levy noticed too and dug up this piece he wrote for Harpers in 1984. If you read nothing else today, read this. First, because we should know where our tools come from, their history and inventors. And second, but not last nor least, because it has wonderful quotes like this:
“The spreadsheet is a tool, and it is also a world view — reality by the numbers.”
The Ethics of Experimenting on Yourself by Amy Dockser Markus. With new companies cropping up to help individuals collect and share their personal data there has been an increased interest in citizen science. A short piece here at the Wall Street Journal lays the groundwork for what may become a contentious debate between the old vanguards of the scientific institution and the companies and citizens pushing the envelope. (The article is behind a paywall, but we’ve archived it here.)
Better All The Time by James Surowiecki. I started reading this thinking it would be another good piece about the digitization of sport performance and training, and it was, but only partly. What begins with sports turns into a fascinating look at how we are succeeding, and in some cases failing, to improve.
Article 29 Data Protection Working Party: Opinion 8/2014 on the Recent Developments on the Internet of Things. Do not let the obscure boring title fool you, this is an important document, especially if you’re interested in personal data, data privacy, and data protection rights. Most interesting to me was the summary of six challenges facing IoT data privacy and protection. I’m also left wondering if other countries may follow the precedents possibly set by this EU Working Party.
30 Little-Known Features of the Health and Fitness Apps You Use Every Day by Ash Read / AddApp. Our friends at AddApp.io put together a great list of neat things you may or may not know you can do with various health and fitness apps.
Man Uses Twitter to Augment his Damaged Memory by John Paul Tiltow. Wonderful piece here about Thomas Dixon, who uses Twitter to help document his life after suffering a traumatic brain injury that severely diminished his episodic memory. What makes it more interesting is that it’s not just a journal, but also a source of inspiration for personal data analysis:
”Sometimes if I have like an hour, I’ll be like ‘How’s the last week been?’“ Dixon says. ”I’ll look at the past week and I’ll go, ‘Oh, okay. I really do want to get a run in.’ So I will use it to influence certain decisions.”
Patients and Data – Changing roles and relationships by David Gilbert and Mark Doughty. Another nice article about the ever-changing landscape that is the patient/provide/insurer ecosystem.
The Quantified Anatomy of a Paper by Mohammed AlQuaraishi. Mohammed is a Systems Biology Fellow at Harvard Medical School, and he’s an avid self-tracker. In this post he lays out what he’s learned through tracking the life of a successful project, a journal publication (read it here), and how he’s applying what he learned to another project.
Calories In, Calories Out by (author unknown). A fascinating post about modeling weight reduction over time and testing to see if said model actually matches up with recorded weight. Not all math and formulas here though,
“I learned several interesting things from this experiment. I learned that it is really hard to accurately measure calories consumed, even if you are trying. (Look at the box and think about this the next time you pour a bowl of cereal, for example.) I learned that a chicken thigh loses over 40% of its weight from grilling. And I learned that, somewhat sadly, mathematical curiosity can be an even greater motivation than self-interest in personal health.”
Fitness Tracker on a Cat – Java’s Story by Pearce H. Delphin. A delightful post here about tracking and learning about a cat’s behavior by making it wear at Fitbit. Who said QS has to be serious all the time?!
100 Days of Quantified Self by Matt Yancey. Matt downloaded his Fitbit Flex data using our data export how-to then set out analyzing and visualizing the data. Make sure to click through for the full visualization.
IAMI by Ligoranoreese. If you’re in San Francisco consider stoping by the Catherine Clark Gallery for this interesting exhibit. The duo, Ligoranoreese, created woven fiber optic artwork based on Fitbit data.
From the Forum
Anyone have a good way to aggregate and visualize data?
Questions about personal health tracking
Call for Papers: special issue of JBHI on Sensor Informatics
Sleep Tracking Device – BodyEcho
We’re back after missing last week (sorry!) with a bit longer list than usual. Enjoy!
Thoughts on Quantified Self for Modifying Long Term Life Goals by Mark Krynsky. Mark, a member of our QS Los Angeles meetup group, is consistently putting together interesting ideas in the QS space. In this short post he explore how QS tools might be used to understand long-term life goals.
Open Data for Open Lands by Alyssa Ravasio. The value of data isn’t confined to what we can understand about ourselves. There is so much beneficial information out there, especially when it comes to public data. In this post, Alyssa makes the case for protecting and promoting open data ideas and concepts regarding out most precious public spaces – the national parks system.
Art at the Edge of Tomorrow: Lillian Schwartz at Bell Labs by Jer Thorpe. A wonderful biographical piece about Lillian Schwartz, a pioneer in the field of computational art and exploration.
Terms of Service by Michael Kelller and Josh Neufeld. A reporter and nonfiction cartoonist team up to use a comic to tell us about the new world of data and privacy we currently inhabit. Interesting format and compelling content!
Narrative Camera by Morris Villarroel. Morris has been wearing a Narrative personal camera for six months. In this short post he explains what he’s learned and experienced over that time.
Where my 90 Hours of Mobile Screen Time in September Went by Bob Stanke. Bob used an app (Trackify) on his Android phone to track how much time he was spending on his phone and what apps he used the most.
Quitting Caffeine by Andrei-Adnan Ismail. Andrei wasn’t happy with his relationship with coffee and caffeine so he he decide to try and quit. Using tracking and really interesting use of “sprints” to gradually reduce his consumption, Andrei was able to quit. Great post here describing his process and the data he gathered along the way (including how his change affected his sleep).
Twitter Pop-up Analytics by Myles Harrison. Myles takes us through the process of downloading, visualizing, and analyzing personal data from Twitter.
Seven Months of Sleep by Eric Boam. A bit of an old one here, but beautiful and informative nonetheless. Make sure to read the accompanying piece by Eric. (I’m also looking forward to seeing more about this dataviz of his Reporter app data soon.)
My latest effort to visualize my calorie intake and weight loss by reddit user bozackDK. Using data collected from MyFitness pal, bozackDK has created this great visualization of his data. I asked what was learned from making this graph and received this wonderful response:
“I make graphs like these to keep myself going. I need some kind of proof that I’m doing alright, in order to keep myself wanting to go on – and a graph showing that I can (somewhat) stay within my set limits, and at the same time showing that it actually works on my weight, is just perfect.”
Two weeks ago we announced the release of the QS Access App so you could access your HealthKit data in tabular format for personal exploration, visualization, and analysis. In that short period of time, we’ve seen a good number of downloads and positive feedback.
We know from our experiences hosting in-person and online communication about personal data that seeing real-world examples of what is possible is what inspires people to engage and ask questions of their own data. With that in mind we’re excited to announce our QS Access Visualization Showcase.
We are looking to you, our amazing community of trackers, designers, and visualizers, to show use what you can do with data gathered from using the QS Access App. Make heatmaps in D3, complete analyses and visualizations in Wizard, or just make meaningful charts in Excel. If you’re visualizing your QS Access data we want to see it.
We also know that data visualization design and creation is not trivial work. To support the community and help expose the visualization work we’ll be awarding free tickets to our QS15 Global Conference & Exposition to individuals who use QS Access to create unique and interesting visualizations. We’ve earmarked two tickets (a $700 value) for outstanding work. If you’re selected, we’ll also work with you to showcase your work at the QS15 Conference and Exposition so other community members and attendees can explore and learn from their own data.
If you’re in the Bay Area come to our QS Meetup on November 11th at the Berkeley Skydeck. You can showcase your visualization and tell our community what you’ve learned from accessing and visualizing your data.
HealthKit is still new and the number of apps that integrate with it is growing by the day. At QS Labs we’ve done a bit of work making simple visualizations that are meaningful to us.
Steps and Sedentary Activity
Gary has an iPhone 5s which has native step tracking. We used the QS Access app to export his hourly step totals and made these simple line graphs in Excel. You can read more about what he learned from these simple data visualizations here.
How Much Do I Run?
Ernesto is an avid runner and enjoys running along the quiet trails in Los Angeles. He was interested to see how often he actually runs and if there’s any pattern to his running. Using a well-designed D3 template he was able to make a calendar heatmatp of his running distance.
If you don’t have any HealthKit data to work with, or just want to play with some example data we’ve created a few files that you can use as examples. Download the files below from our GitHub account and make sure to read the documentation to understand where the data is coming from. Descriptions of the data files and sources are available in our QS Access Data Examples repo on Github.
It’s link-apolooza time! Enjoy these great news pieces, blog posts, personal data stories, and visualizations.
Robert Wood Johnson Foundation Launches Initiative to Assess How Data Can Be Used to Improve Health by RWJF Staff. Some exciting news coming out of RWJF this week about their new program to explore how individuals and communities are using health data and information. Don’t forget to read the accompanying blog post to learn more.
“For These Times”: Dickens on Big Data by Irina Raicu. Who knew the philosophical debate on a life governed by measurable facts had such a pedigree!
How and Why We Are Working with the FDA: Background and a Brief Summary of the Recent Meeting with the FDA about the Nightscout Project by Scott Leibrand. We’re big fans of the Nightscout project here at QS Labs. It’s great to seem them moving forward with a productive dialogue with the FDA.
Sir Tim Berners-Lee Speaks Out on Data Ownership by Alex Hern.
The data we create about ourselves should be owned by each of us, not by the large companies that harvest it, Tim Berners-Lee, the inventor of the world wide web, said today.
Sensors and Sensibility by Andrew Leonard. One day we might look back at our fears of insurers nefariously using our data to adjust premiums. Until then, that fear is alive and real. Thorough reporting here from the new Backchannel.
One Quantified Self App To Rule Them All by Chris Roth. As Chris explored the growing QS space and worked on his own open-source logging app he noticed a few things. Read on to see his take on where the space should be evolving.
Quantified Health and Software Apps by Sara K. Moir. What started as a Tweetstorm about her experience with MyFitnessPal expanded into a great exploration about what it means to be a user (and designer) of health behavior tracking tools.
How Text Messages Change from Dating to Marriage by Alice Zhao. Only a data scientist would celebrate a six-year anniversary with a thoughtful and thorough analysis of their communication. Alice did a great job here showing what’s changed over the years as her and her husband have moved from courtship to marriage.
Losing 58.3 Lbs For Science by Zachary Townsend. Zachary just finished up his participation in the One Diet Does Not Fit All: Weight Loss study. Over the last year he’s lost nearly 60lbs and learned a lot about himself and his diet.
Using JSL to import BodyMedia Fit Activity monitor data into JMP by Shannon Conners. We featured Shannon’s amazing visualization work in our September 20th edition of What We’re Reading. She returns here with a thorough how-to on how to explore BodyMedia and MyFitnessPal data in JMP. Even as a non-JMP user I was delighted to find out about the MyFitnessPal Data Downloader Chrome Extension she used to download her meal data.
My Up Skyline for the Week by Abe Gong. Abe is a data scientist at Jawbone was taking a look at his own activity data and decided to use the then new Jawbone API to download his data and make some interesting visualizations.
Your Life on Earth by the BBC. Not a typical QS visualization, but unique and interesting to see what’s happened in and around the world over the course of your life.
I’ve been exploring upgrading my data visualization skills by learning D3. If you’re in the same boat or want know someone who is then you can point them towards this great intro from the engineers at Square.
From the Forum
Today’s Number is 35: The age of the spreadsheet!
A long one this time. Enjoy the words, numbers, and images herein.
New biometric tests invade the NBA by Pablo S. Torre and Tom Haberstroh. Data and statistics are nothing new in professional sports. They’ve even made Academy Award nominated movies based the idea that data can help a team win. Until now data on players and teams has come from analysis of practices and gameplay. This great piece opens another discussion about collecting even more personal data about how players in the NBA live their lives off the court. Recall that athletes, coaches, and owners have been talking about out of game data tracking since 2012.
Misleading With Statistics by Eric Portelance. We’ve featured these type of articles before, but the example used here by Eric is not to be missed. So many times the data visualization trumps the actual data when a designer makes editorial choices. After reading this piece you’ll think critically the next time you see a simple line chart.
Handy Tools & Apps by Ray Maker. A great resource for athletes and exercisers who use a variety of tools to capture, export, and work with the activity and workout data we’re collecting.
Happiness Logging: One Year In by Jeff Kaufman. A great post here about what Jeff has learned about himself, what is means to log something like “happiness”, and the power of tagging data. After looking at his data, and a commenter’s from the r/quantifiedself subreddit, I’m wondering about the validity of 10-point scales for this type of self-tracking.
Redshit/f.lux Sleep Experiment by Gwern. Our esteemed friend and amazing experimenter is back with another analysis of his sleep data. This time he explains his findings from using a program that shifts the color temperature on his computer away from blue and towards red.
I ran a randomized experiment with a free program (Redshift) which reddens screens at night to avoid tampering with melatonin secretion and sleep from 2012-2013, measuring sleep changes with my Zeo. With 533 days of data, the main result is that Redshift causes me to go to sleep half an hour earlier but otherwise does not improve sleep quality.
Make sure to join the discussion on the forum!
Schedule Abstracted by Mike McDearmon.
Even a hectic schedule can have a sense of serenity with all text, labels, and interface elements removed.
Location History Visualizer by Theo Platt. The data above is actually my full Location History from Google Takeout. Theo made this simple and fast mapping visualization tool. Try is out yourself!
Lifelogging Lab. No visualizations here, but if you’re a designer, visualizer, or just have some neat data then you should submit it to this sure to amazing curated exhibition.
From the Forum
The ethics of QS
Call For Papers: HCI International 2015 Los Angeles
Pebble for Fitness Tracking
QS Business Models
QS, Light, Sleep, Reaction Timing, and the Quantified Us
Are you using your data to write a reference book or tell a story?
At our 2013 Quantified Self Global Conference we were excited to share a variety of beautiful and insightful data visualizations from our community. In the months leading up to the conference we asked attendees to send in their own personal data visualizations along with a short description. In our 6 years of hosting Quantified Self meetups and events, as well as running this website, our forum, and social channels, we’ve seen the power of data visualization as a story telling medium. We exist in part to help people tell their stories – about the data they collect, the changes they create, and the insights and new knowledge they’re excited to share.
Today we’re sharing a few of our favorite visualizations from past conferences. The images and descriptions below represent a wide a variety of tracking experiences and techniques, and we hope to showcase eve more unique personal data projects at our upcoming QS15 Conference & Exposition.
Tracking Sleep by Anita Lillie
This is concatenation of screenshots from my sleep app. Most sleep apps don’t let you zoom out like this and still see daily/nightly detail, so I just made it myself. I like that it shows how almost-consistent I am with my sleep, and made me ask new questions about the “shape” of a night of sleep for me.
2.5 Years of My Weight by Mette Dyhrberg
I gained a lot of insights from this heat map. The most obvious weight gain was no surprise — that’s when I periodically don’t track. In any case, the big picture patterns are easily identified with a heat map. Realized looking at this heat map that the point of no return was mid-April 2012 — my data shows that was when I switched protein shakes with an egg based breakfast. I have since experimented and seen that protein shake in the morning seems to keep my blood sugar more stable and as a result my weight under control!
One Month of Blood Sugar by Doug Kanter
This is a visualization of one month of my blood sugar readings from October 2012. I see that my control was generally good, with high blood sugars happening most often around midnight (at the top of the circle).
Tracking Productivity by Nick Winter
My percentile feedback graph of my development productivity helps my motivation.
Six Months of My Life by David El Achkar
This is my life during the past six months. Each square = 15 minutes. Each column = 1 day. This picture represents 138 days or 3,000+ activities.
My Thesis Self Portrait by Sara M. Watson
Here’s a period of a few days of webcam images taken using Stan James’ LifeSlice during the final days of editing my thesis on Quantified Self uses of personal data. Serious business!
Sleep and Meaningful Work by Robby Macdonell
In an average work day, I don’t consider communication (email, instant message, etc) to be terribly meaningful work. I’d much rather be working on building software. Getting more sleep the night before increases the amount of meaningful work I’m likely to do in a day.
70 Days of Pulse by Laurie Frick
Pulse rate over 24 hours for 70 days from my Basis watch. Grey=null, blues=85
Enjoy this week’s list!
Effect of Self-monitoring and Medication Self-titration on Systolic Blood Pressure in Hypertensive Patients at High Risk of Cardiovascular Disease by Richard McManus et al. An interesting research paper here about using self-monitoring to reduce blood pressure. The paper is behind a paywall, but since you’re nice we’ve put a copy here.
Apple Prohibits HealthKit App Developers From Selling Health Data by Mark Sullivan. Some interesting news here from Apple in advance of their new phone and possible device release in a few weeks. I applaud the move, but would like to see more information about data portability in the next release.
Science Advisor, Larry Smarr by 23andMe. Great to hear our friends 23andMe and Larry Smarr are getting together to help work on understanding Inflammatory Bowel Disease. If you’ve been diagnosed with Crohn’s disease or ulcerative colitis consider joining the study.
Personal Health Data: It’s Amazing Potential and Privacy Perils by Beth Kanter. A lot of people have been talking recently about the privacy implications of using different tracking tools and technologies. In this short post Beth opens up some interesting questions about why we might or might not open up our personal data to others. Make sure to read through for some insightful comments as well.
Let’s Talk About 3 Months of Self-Quantifying by Frank Rousseau. Frank is one of the founders of Cozy Cloud, a personal could service. He’s also designed Kyou a custom tracker system built on top of Cozy. He’s also been using the services to track his life. In this post he explain how tracking his activity, sleep, weight, and other habits led to some interesting insights about his behavior.
The iPhone 5S’ M7 Predictor as a Predictor of Fitbit Steps by Zach Jones. A great post here by Zach as he explores the data taken from his iPhone 5S vs. his Fitbit.
Using Open Data to Predict When You Might Get Your Next Parking Ticket by Ben Wellington. Not strictly a personal data show&tell here, but as someone who suffers from street sweeping parking tickets somewhat frequently I found this post fascinating. Now to see if Los Angeles has open data…
What Time of Day Do People Run? by Robert James Reese, Dan Fuehrer, and Christine Fennessay. Runners World and Runkeeper partnered to understand the running habits of runners around the world. Some interesting insights here!
What Happens When You Graduate and Get a Real Job by Reddit user matei1987. A really neat visualization of min-by-min level Fitbit step data.
Data + Design by Infoactive and the Donald W. Reynolds Institute. A really interesting and unique take on a data visualization book. This CC-licensed, open source, and collaborative project represents the work of many volunteers. I’ve only read through a few chapters, but it seems to be a wonderful resource for anyone working in data visualization.
Want to receive the weekly What We Are Reading posts in your inbox? We’ve set up a simple newsletter just for you. Click here to subscribe. Do you have a self-tracking story, visualization, or interesting link you want to share? Submit it now!
Lee Rogers has been collecting data about himself for over three years. The daily checkins, movements, and other activities of his life are capture by automatic and passive systems and tools. What makes Lee a bit different than most is that he’s set up a personal automation system to collect and make sense of all that data. A big part of that system is creating an annual report every year that focuses on his goals and different methods to display and visualize the vast amount of information he’s collecting. In this talk, presented at the Bay Area QS meetup group, Lee explains his data collection and why he values these annual snapshots of his life.
Cors Brinkman is a media artist and student. In June of 2013, he started a project to keep track of himself. He decided to start with LifeSlice, a tool to have your computer keep track of your behavior by taking a picture, screenshot, and location data every hour. After experimenting with that system Cors added in mood tracking to round out his data collection. In this talk, presented at the 2014 Quantified Self Europe Conference, Cors describes his process and some of the interesting ways he visualized and analyzed his thousands of self-portraits.