Tag Archives: visualization

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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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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Anand Sharma: Aprilzero, Gyroscope, and Me

AprilZero
With all the self-tracking applications, devices, and services out there it can be hard to make sense of all the data you’re collecting. Anand Sharma ran into this situation in 2014 when he started thinking about his data and how he wanted to use it to help him understand himself, optimize what he cared about, and help him tell the story of his life through data. He tackled this problem by creating a personal website called Aprilzero that let him publicly expose his data and insights. After a large influx of positive feedback Anand, along with a few collaborators, has launched Gyroscope, which enables individuals to use his visualization and aggregation system. We were excited to have Anand at our Bay Area meetup group a few months ago, where he told us the story of hw this all came together and what he’s been learning in the process.

To learn more about Anand, and his journey to create Aprilzero and Gyroscope check out his journal.

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The Art of Self-Tracking

On June 20th we’re inviting the public to join us for the first ever Quantified Self Expo. It’s going to be a full day of dedicated to showcasing amazing QS tools with multiple demos, talks, how-to sessions, and exciting experiences. But that’s not all.

We’re excited to host, as part of the Expo, an exhibition focused on data as art. In the words of our co-curators, Alberto Frigo and Jacek Smolicki:

Art of Self-Tracking is an exhibition gathering a number of international artists who use different personal data tracking techniques in their artistic practices.

Ranging from meticulously composed manual diaries, hand-drawn representations of every meal consumed on daily basis to sonification of geo-locational data and 3D renderings of shapes recognised in clouds, the exhibition aims to highlight the plurality of perspectives on self-tracking.

We’re honored to be hosting the following artists and their amazing work (which you can see a few previews of below):

Alberto Frigo (IT/SE), Brian House (US), Catherine D’Ignazio (US), Daniel Peltz (US), Davide Di Saró (IT/CA) & Kristy Trinier (CA), Elly Clarke (UK/DE), Ellie Harrison (UK), Giovanni Meneguzzo (IT), Ingrid Forsler (SE)
Borítás Viktor alias Iwan Wilaga (HU/HK) , Jacek Smolicki (PL/SE), Jacopo Pontormo (IT), James Pricer (US), Janina Turek (PL), Morris Villarroel (CA/ES), Stephen Cartwright (US), and Yann Vanderme (FR).

Alberto Frigo

Alberto Frigo

Brian House

Brian House

Daniel Peltz

Daniel Peltz

Elle Harrison

Elle Harrison

Giovanni Meneguzzo

Giovanni Meneguzzo

Ingrid Forsler

Ingrid Forsler

Iwan Wilaga

Iwan Wilaga

Jacopo Pontormo

Jacopo Pontormo

James Pricer

James Pricer

Morris Villarroel

Morris Villarroel

Stephen Cartwright

Stephen Cartwright

To see the artwork for yourself we invite you to join us on the 20th. It’s going be a wonderful event.

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Anna Nicanorova: My Year in Numbers

AnnaNican_2014

Anna Nicanorova is a data scientist. Starting in 2013 she started making an annual report, but what stuck by how difficult it was to access her own data she was collecting through different apps and services. Early this year she put together her 2014 annual report based on a few different tools and using If This Then That as a data backup service. In this short talk, presented at the New York QS meetup group, Anna describes her process, her data, and what she learned from examining a year in numbers.

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QS15 Conference Preview: Evan Savage on Data Sense

On June 18-20 we’ll be hosting the QS15 Conference & Expo in San Francisco at the beautiful Fort Mason Center. This will be a very special year with two days of inspiring talks, demos, and discussion with your fellow self-trackers and toolmakers, plus a third day dedicated to the Activate Exposition. As we start to fill out our program we’ll be highlighting speakers, discussion leaders, sponsors, and attendees here.

evan-headshotEvan Savage is an ex-Facebook full-stack engineer turned personal data, education, and persistent gameplay hacker/entrepreneur. Currently, he is working on Data Sense, a web-based tool to make personal data analysis accessible to the rest of us. Evan is also an avid cyclist, decent cook/homebrewer, and an occasional electronic music composer.

Evan will be showcasing Data Sense during one of our two Lunchtime Ignite sessions. During his presentation he’ll talk about the making of Data Sense using screenshots of visualizations from Data Sense itself. He’ll also touch on broader ideas and lessons for helping non-technical users understand their data through visualization. Here’s a preview of a Data Sense visualization of Evan’s Facebook posting and music-listening habits during several months of development time:

We’re excited to have Jamie joining us at QS15 and asked him a few questions about himself and what he’s looking forward to at the conference.

QS: What is your favorite self-tracking tool (device, service, app, etc)?

Evan: As Luddite as it sounds, some of my most life-altering data-driven changes have come from simple pen-and-paper tracking. It’s about as close to universally accessible as you can get: the only barriers to entry are pen, paper, and basic writing/literacy skills. Compare that with websites (<3B users) or smartphone apps (<2B users).

OK, that’s sidestepping the question. As a geek, I have to admire IFTTT; they’re essentially teaching programming/UNIX concepts by stealth! That, and their list of supported services is impressive.

QS: What are you most looking forward to at the conference?

Evan: This is super-specific, but: Stephen Cartwright’s kinetic data sculptures. Believe it or not, those sculptures were my first exposure to the QS community at large. Before that, I’d been self-tracking to help address panic/anxiety issues, and decided to attend QS12 on a lark. I walked into the atrium, saw this moving rod sculpture physically stepping through timeseries datasets, and knew that I’d come to the right place.

There are very few boundaries around what is and is not QS – which is great! It’s a radical inclusiveness that was incredibly welcoming when I first joined, and it’s absolutely worth preserving.

QS: What should people come talk to you about at the conference?

Evan: Well, I’m co-organizing the breakout session on data visualization…
As for interests: education (see below), gameplay (in some sense, QS is the ultimate immersive game), data ownership (do you truly own your data if you can’t understand it?)… but really, if you have something interesting to say – and we all do – I’m eager to hear it.

QS: What tools, devices, or apps do you want to see at the conference?

Evan: An intracorporeal sensor for reliable food tracking that doubles as a tricorder.
More seriously: I’d love to see a section of floor for the hardware/sensing hackers, a space to really interact with these projects where QSers are building wireless weight scales from scratch, reverse-engineering Fitbits, hacking exosenses and real-time feedback, etc. This would be similar to the visualization gallery: a celebration of the awesome, quirky, and highly personal things that our fellow QSers are up to.

QS: What topic do you think that Quantified Self community is not talking enough about?

Evan: Data literacy. There’s a pernicious assumption that “the average user” can’t or doesn’t want to understand their own data: it’s too technical, people have limited attention spans, etc. It has to be pre-chewed and regurgitated at them, a sort of dataviz pablum. Word clouds and chartjunk dashboards abound.

QS could be a powerful tool for making data literacy relevant. Think of it as the core of a science/stats curriculum for the digital age, one students might actually relate to, and you’ve got the idea.

Evan’s session is just one of the many hands-on, up-to-date, expertly moderated sessions we’re planning for the QS15 Global Conference and Exposition. Register here!

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QS15 Conference Preview: Stephen Cartwright on 17 Years of Location Tracking

On June 18-20 we’ll be hosting the QS15 Conference & Expo in San Francisco at the beautiful facilities at the Fort Mason Center. This will be a very special year with two days of inspiring talks, demos, and discussion with your fellow self-trackers and toolmakers, plus a third day dedicated to the Activate public expo. As we start to fill out our program we’ll be highlighting speakers, discussion leaders, sponsors, and attendees here.

Steve4bStephen Cartwright has been attending the QS Conferences since 2012, where he first spoke about his ambitious geolocation tracking project. As an associate professor at the School of Art and Design at the University of Illinois at Urbana-Champaign, where he teaches sculpture, digital fabrication, and furniture design, Stephen brings an interesting and welcomed point of view and set of experiences to our show&tell program.

At the QS15 Conference he will be sharing his process and what he’s learned from tracking his location every hour using a GPS for the last 17 years. He will describe how his practice has changed and adapted to new technologies over the years, including how active versus passive tracking techniques have impacted this project.

My tracking informs my life and especially my art, so I will consider my tracking through the lens of my 3D data visualization sculpture. The artistic aspect of my work allows the data visualization to become more than informative graphs, they become new landscapes of data.

P1090611b

We’re excited to have Stephen joining us and asked him a few questions about himself and what he’s looking forward to at the conference.

QS: What is your favorite self-tracking tool (device, service, app, etc)?

Stephen: This is a difficult question, I use different tools for different stages of my work. My practice would be nowhere without a GPS. It took me a long time to replace my Garmin stand-alone GPS but I now use the MotionX GPS app for my iPhone. My requirements for these apps/devices is that the waypoints have to be saved with the date and time attached.

QS: What are you most looking forward to at the conference?

Stephen: The conference is a great place to be among like-minded people and share ideas and inspiration. Although all the attendees have a lot in common everyone comes to self-tracking from a different angle and seeks different outcomes. I love to see how similar practices result in improvements in performance and health, self-help, and even art.

QS: What should people come talk to you about at the conference?

Stephen: Come talk to me about the intersection of art and science, data-visualization, and GPS/location tracking.

QS: What tools, devices, or apps do you want to see at the conference?

Stephen: I am looking for the best smart phone based step and movement tracker.

QS: What topic do you think that Quantified Self community is not talking enough about?

Stephen: I would like to hear more about the relationship between individual trackers and larger data studies. How well do we know ourselves as compared to what can be inferred about us by our data footprint or studies of people in similar circumstances?

Stephen’s session is just one of the many hands-on, up-to-date, expertly moderated sessions we’re planning for the QS15 Global Conference and Exposition.

Register here!

Bonus Video of Stephen’s Data:

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What We Are Reading

We’ve put together an extra-long list for our last What We’re Reading of 2014. Enjoy!

Articles
Medical Inhalers To Track Where You Are When You Puff by Alison Bruzek. We’ve been following Propeller Health (nee Asthmapolis) for quite a while and this piece does a good job outlining their technology and promise.

How Self-Tracking Apps Exclude Women by Rose Eveleth. A great article on the issues brought on by the gendered design of self-tracking tools and applications. Good to see thoughts and experiences from some of our QS community members included in the piece. (If you’re a woman interested in women’s only QS meetups there are groups in New YorkBoston, and San Francisco.)

The Echoes of Hearts Long Silenced by Ron Cowen. Humans have been curious about the sounds our bodies make for centuries. What could we learn from tracking and recording those curious buh-bumps? Sprinkled throughout this great article are examples of the the power of hearing and recoding the human heart.

The Genetic Self by Nathaniel Comfort. A great longer read on the ever expanding role personal genetics can have on our life, especially our health.

This brave new world need only be dystopian if we surrender our agency. If we are aware of the exchanges we are making and how our information is valued—if we are alert to the commodification of personal data—we can remain active players instead of becoming pawns.

More Data, Fewer Questions by Jer Thorp. “Every headline about data from the NYTimes containing a question, from 2004–2014.” (Part of an outstanding collection of predictions for the future of journalism in 2015] curated by the Nieman Lab.)

Dada Data and the Internet of Paternalistic Things by Sara M. Watson. A great piece of speculative fiction here that “explores a possible data-driven future.”

Tech Giants Move to Protect Wearables by Ashley Gold. With more wearables and QS tools capturing personal health data there is increasing scrutiny on privacy and protection, especially at the federal level.

Make Your Own Activity Tracker by Young-Bae Suh. Want to track your activity, but also love DIY projects? This is the one for you. A great walk through, including sample code, to get you up and running with a wrist-based activity tracker.

Enviro-Trackers Are a New Gadget Trend. What Do We Do With Them? by Margaret Rhodes. What can we do with personal environmental data? Margaret explores this question in the wake of the new devices currently available and being developed to track the world around you.

Vicious Cycle by Patt Virasathienpornkul. A fun student project that imagines a close-loop system of calorie consumption and expenditure.

Show&Tell

musicviz.006-1024x576Music Records by Salem Al-Mansoori. A wonderful deep dive into eight years of music listening history. Salem supplements the raw listening data with additional information and creates an amazing set of visualizations to answer questions such as, “Where do the artists I listen to come from?” and “How are my tastes changing over time.”

Half a Year with Dash by Colin Sullender. When the Dash OBD tracking device connected with the IFTTT service in mid 2014 Colin began logging each of this car trips. In this post he gets into the data to see what he can learn from his driving data.

Visualizations

MapboxRunkeeperSuperpowering Runkeeper’s 1.5 Million Walks, Runs, and Bike Rides by Garrett Miller. The folks at Mapbox have done it again by improving on their last map collaborations with Runkeeper. Make sure to poke around in the large map to see where people are running, riding, and walking in your area. Also see this interview/article if you’d like to learn a bit more about the project.

Moves_HomeWorkA Year in Moves Data by Patrick Maloney. Patrick graphed his tie spent at time and at work by access his Moves data.

Runkeeper_DashboardCrowdsourcing a Runkeeper Dashboard by Patrick Tehubijuluw. Patrick built a nice overview data dashboard to explore his Runkeeper data. If you’re a QlikView User you can download and play with your own data.

Tell, Don’t Show by John Pavlus. Data dashboards are all the rage in our mobile-focused personal data world, but do they do a good job conveying information? John Pavlus argues that “data verbalization” is the next big user experience.

From the Forum
Understanding Goal Setting and Sharing Practices Among Self-Trackers
Wearable Timelapse Camera? (For time management)
New book about Quantified Self, called Trackers
Determine your Fitbit stride length using a GPS watch

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What We Are Reading

Enjoy this week’s list!

Articles
Flipping Primary Health Care: A Personal Story by Kedar S. Mate and Gilbert Salinas. We’re leading off this week with a fascinating case study that describes what happened when one patient, Gilbert Salinas, “flipped the clinic.” After deciding to accept fellowship that would move him from California to Cambridge, MA he worked with his care team to take control of many of the tasks typically performed in the clinic.

Most importantly, I feel happier and healthier, and I am amazed that I have been able to accomplish my goal of being healthy during this year away from my providers. It has transformed my sense of what is possible and has encouraged me to take further ownership of my health.

A Case for Autonomy & The End of Participatory Medicine by Hugo Campos. I’m constantly in awe of our friend and QS community member, Hugo Campos. As a leader in the fight for access to personal data (see this great NPR piece from 2012) he’s been an inspiration for our own ongoing Access Matters work. In this post, Hugo makes the case for focusing less of patient participation in the medical system, and re-orienting towards improving patient autonomy and self-determination.

Health Data Outside the Doctor’s Office by Jon White, Karen DeSalvo, and Michael Painter. In this short post, the smart folks at RWJF introduce the new JASON group report, Data for Individual Health, which

“[…] lays out recommendations for an infrastructure that could not only achieve interoperability among electronic health records (EHRs), but could also integrate data from all walks of life—including data from personal health devices, patient collaborative networks, social media, environmental and demographic data and genomic and other “omics” data.”

A Systematic Review of Barriers to Data Sharing in Public Health by Willem van Panhuis and colleagues. In this review article, the authors outline twenty specific barriers standing in the way of sharing data that could improve global public health programs. They include numerous examples of the technical, motivational, economic, political, legal, and ethical barriers that prevent more sharing across public health systems.

#WeAreNotWaiting at the Fall 2014 D-Data ExChange: The Stars Are Aligning by Mike H. QS Labs was unfortunately unable to attend the Fall 2014 D-Data ExChange, but were excited to read this great summary of the event.

Show&Tell
The Quantified Self and Humanities Best Friend by Kevin P. Kevin found out that he could track his dog, Lilo, along with himself when he went for walks and runs. In this short post he outlines his process, and the barriers he ran into, for collecting data from his different devices to show his progress on a recent 5k walk.

Follow-up study: on the working time budget of a university teacher. 45 years self-observation pdf hereby Dimitar Todorovsky. Dimitar is a recently retired researcher and professor of Chemistry and Pharmacy at the University of Sofia in Bulgaria. In this journal article he outlines his findings from tracking his time every day over his 45-year career. Most striking to me is that he averaged 10hr of work per calendar day for the entire 45-year period.

Visualizations
HR_proposal
Heart Rate (bpm) during marriage proposal by reddit user sesipikai. Going to Rome to surprise your fiancé to be? Why not record your excitement and nervousness by wearing a heart rate chest strap!


To Big to Fail by Nicholas Felton. In this great video presentation Nicholas Felton describes the process behind building the latest in his series of Annual Reports. You can also check out the full 2013 Annual Report here.

From the Forum
Counterintuitive HRV Measurements
Active, Athletic Folks With Asthma Tracking Their Performance
Mobile Health and Fitness Apps Privacy Study
OP Innovations Sensors
Hexoskin
Timer/logger/tracker–what kind of gadget am I looking for?

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What We Are Reading

We had a lot of fun putting together this week’s list. Enjoy!

Articles
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.

Show&Tell
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?!

Visualizations
MattYancey_Fitbit
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_jpg
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.

List of Physical Visualizations. I can’t say it any better than Mortiz Stefaner: “Remember that epic list of data sculptures and physical data visualizations? Well, it became more epic.

From the Forum
Anyone have a good way to aggregate and visualize data?
Questions about personal health tracking
Hello QS
Call for Papers: special issue of JBHI on Sensor Informatics
Sleep Tracking Device – BodyEcho

 

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