Tag Archives: visualization

What We Are Reading

It’s link-apolooza time! Enjoy these great news pieces, blog posts, personal data stories, and visualizations.

Articles

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.

Show&Tell

AZ_timetext2
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.

ZT_Weight_small
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.

Visualizations
AG-weekly-skyline-graph
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.

ER_SolarEclipses
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

Decode Your Chronic Illness
The Ethics of QS
Tasks & Measures
Lifelogging to Prevent Depression
Wearable Body Temperature Tool
Sleep Apnea Treatments
Looking for Android Time Tracking App

Today’s Number is 35: The age of the spreadsheet!

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What We Are Reading

A long one this time. Enjoy the words, numbers, and images herein.

Articles
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.

You are not your browser history by Jer Thorpe. If someone you didn’t know was given a record of every ad served to you in your browser, what would they say about you? Who would they think you were? Jer Thorpe actually put these questions to the test as part of his work with the Floodwatch project. Floodwatch is a very interesting tool (browser extension) that saves and visualizes the adds you see while you browse. They also have a clear privacy policy including giving you access to your data.

Show&Tell
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!

Visualizations

Joost_3yr
3 Years of computing by Joost Plattel. Our good friend and Amsterdam QS co-organizer, Joost Plattel takes a look at three years of running Lifeslice.

ScheduleAbstracted_MMcD
Schedule Abstracted by Mike McDearmon.

Even a hectic schedule can have a sense of serenity with all text, labels, and interface elements removed.

LocationHistory
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?

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Visualizing Our Quantified Self

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

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QS | Public Health Symposium: Doug Kanter’s Healthiest Year

We’ve featured the work of our friend and QS community member, Doug Kanter, many times here on the Quantified Self website and we were excited to have him participate in our Quantified Self Public Health Symposium. Doug is both a toolmaker and self-tracker, focusing primarily on using his experience with tracking his diabetes-related data to inform new tools and methods. In this talk, Doug explains what he learned from diving headfirst into a year-long project of tracking and visualizing all of the data he could gather about his diabetes self-management, his diet and activity, and other important factors. Beyond the wonderful visualizations he shared, Doug helped highlight something many patients and self-trackers are struggling with, the inability to access data easily and the lack of interoperability among data services and devices. We invite you to watch Doug’s wonderful talk below.

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What We Are Reading

Enjoy this week’s list!

Articles
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.

Show&Tell
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…

Visualizations
RWTime
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!

FitbitMin
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.

DataDesign
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.

From the Forum
Good Morning World!
Quantified Chess
New Activity Tracker to Replace BodyMedia?
Indirect Mood Measures
OPI TrueSense for Sleep Tracking

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!

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Lee Rogers: Why Annual Reporting

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.

You can read a transcript of Lee’s excellent talk here and view his 20112012, and 2013 reports on his website.

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Cors Brinkman: Lifelog as Self-Portrait

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.

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Laurie Frick: Experiments in Self-tracking

As much as we talk about self-tracking being about health or fitness. . . I think it’s about identity. I think it’s about us. It’s about seeing something meaningful in who we are.

Laurie Frick is a self-tracker and visual artist. It this unique combination that has led her down a path of learning about herself while using the data she collects to inform her artistic work. What started with time and sleep tracking rapidly expanded to included other types of data. In this short talk, presented at the 2014 Quantified Self Europe Conference, Laurie explains how her past experiences have informed her new way of thinking about data, “Don’t hide. Get more.”

If you’re interested in Laurie’s artistic work I highly recommend spending some time browsing the gallery on her website.

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What We're Reading

Enjoy this week’s list!

Articles
CGM in the Cloud: Personal Preferences by Kerri Sparling. A great blog post here by Kerri who explains why it’s so important to have access to her blood sugar data. She’s part of a growing community of people with diabetes who are using different methods to broadcast their CGM data into the could.

On Minorities and Outliers: The Case for Making Big Data Small by Brooke Foucault Welles. The rush towards finding the answers in “Big Data” might lead to the continued exclusion of the women, minorities, and the “outliers” of the world. Brooke makes the case here for examining these “small datasets”  to give them the weight they deserve.

“When women and minorities are excluded as subjects of basic social science research, there is a tendency to identify majority experiences as “normal,” and discuss minority experiences in terms of how they deviate from those norms . In doing so, women, minorities, and the statistically underrepresented are problematically written into the margins of social science, discussed only in terms of their differences, or else excluded altogether.”

Here’s Looking at You: How Personal Health Information Is Being Tracked and Used [PDF] by Jane Sarashon-Kahn. In this report, from the California Healthcare Foundation, Jane lays out how our health data is being acquired and used, for commercial and public benefit. I especially liked the emphasis on privacy, or lack there of.

The Making of April Zero by Anand Sharma. Anand details his journey from starting to self-track to creating an amazing website that serves as his personal QS dashboard. One interesting bit is that his tracking activities increased dramatically after Apple’s M7 chip came out with the iPhone 5S and he noticed that his phone’s battery took much less of a hit from running apps that track his activity in the background.

Show&Tells
Tracking Upset and Recovery by Paul LaFontaine. Paul has been using the Heartmath stress monitor to help him record and understand what causes him to get upset (fall out of coherence). In this post, he details how his recovery method has helped him progress, recover, and slightly reduce the number of upsets during his working session. I recommend reading all of Paul’s great posts on this work.

Europe Honeymoon by reddit user Glorypants. This reddit user tracked his European honeymoon with the Moves app and then used our How to Map Your Moves Data post to learn how to make some great maps to share his experience.

Visualizations
Lillian_YIR
This Year in Numbers – 2014 by Lillian Karabaic. A great “year in review” post here that details the tracking Lillian has done from July 2013 to July 2014. I love the mix of hand-drawn and computer-generate visualizations that provide insight into Lillian’s sleep, diet, cycling, mood, and communication data. (Editor’s Note: Lillian sent this link via the comments on Quantifiedself.com. If you have something to share please let us know!)

HelpMeViz
HelpMeViz.com. I wanted to highlight this great website and community project as we have many great visualization and data scientists in our community. On the HelpMeViz website people submit their visualizations for feedback and assistance. I’ve had fun interacting with the growing community and have even learned a few neat tricks in the process.

TravisHodges
The Quantified Self by Travis Hodges. Travis is a portrait photographer based in London. For his newest project he sought out fifteen individuals who are using self-tracking to understand and improve themselves. I especially like the inclusion of the data visualizations coupled with the individual stories from these self-trackers.

TwitterViz
Visualizing Your Twitter Conversations by Jon Bulava. Jon, a Developer Advocate at Twitter, put together a wonderful how-to for getting started on visualizing your friend network on Twitter. (If you’re interested in using the new Twitter Analytics data to better understand your tweeting we suggest Bill Johnson’s great how-to.)

From the Forum
Data Aggregation
Smart Mirror with Health Sensors
Garmin Vivo Activity Tracker – Your Results?
Sleep Tracking for New Parents

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What We Are Reading

We’ve compiled another list of interesting personal data and Quantified Self articles, self-tracking stories, and data visualizations. Enjoy!

Articles

Experimental evidence of massive-scale emotional contagion through social networks by Adam Kramer, Jamie Guillory, and Jeffrey Hancock. Facebook engaged in a large study to see if emotional states could be transferred/changed via the emotional content of the News Feed. A lot of hubbub recently about this research article related to what it means to knowingly consent to research.

Who Owns Your Personal Data: The Incorporated Woman. Jennifer Morone has added herself to a long list of individuals making a statement against the commercialization of personal data. What started as a design assignment has morphed into a statement against others profiting and controlling personal data. (Immediately remind me of this Kickstarter project.)

Quantified Self and the Ethics of Personal Data by Ian Forrester. Ian does a great job here of exploring current conversations about the variety of ethical questions that come with creating, using, and owning personal data.

Visualizing Algorithms by Mike Bostock. Mike is the creator and steward of the d3.js data visualization library. In this fascinating post, he recounts one of his recent talks about how visualization can be used to understand how algorithms work.

“[...] algorithms are also a reminder that visualization is more than a tool for finding patterns in data. Visualization leverages the human visual system to augment human intellect: we can use it to better understand these important abstract processes, and perhaps other things, too.”

Biometric Shirt for Astronauts Gets Antarctic Tryout by Eliza Strickland. Eliza describes a “try-out” for using self-tracking technology to better understand vital signs and activity during space travel.

Show&Tell

My Solution for Quantified Self: Prompted Data Aggregation by Jonathan Cutrell. Jonathan decided to build his own simple system for self-directed data collection prompts. “While they may be simple data points, and while the questions will repeat, the concept is simple: my computer asks me a question, and tracks my answer for me.”

Quantified Splunk: Tracking My Vital Signs by David Greenwood. David describes how he uses Splunk, a data monitoring and analysis tool, to help him track and make sense of new personal health data he’s collecting. It will be interesting to see what he learns as he starts adding and exploring more of his self-tracking data.

How I Wrote 400K Words in a Year by Jaime Todd Rubin. In March of 2013, Jaime decided he was going to try and write every day. In this post he describes some of the lessons he learned through tracking his writing practice. I was particularly drawn to his methods for tracking all his writing through Google Docs.

Do you have a self-tracking story you want to share? Submit it now!

Visualizations

Withings-via-IFTTTCharting Withings Data Using IFTTT, Google Spreadsheets, and d3.js by Dan Harrington. Dan didn’t like the way Withings presented weight data in it’s visualization. So, he put together a tutorial to show how you can grab your Withings data via IFTTT, import it into a Google Spreadsheet, then visualize it using d3.js, an open-source data visualization library.

 

 

MapRunKeeper1.5 Million Walks, Runs, and Bike Rides by Mapbox and RunKeeper. The Mapbox team worked with Runkeeper to map publicly shared routes. Really interesting to zoom around the world map to see where people who use RunKeeper are exercising.

 

 

Do you have a QS data visualization you want to share? Submit it now!

From the Forum

HealthKit
Lifelogging via Calendar Application
Help Analyzing Text Files?
Breakout: Productivity Tracking

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