What We Are Reading

Enjoy this week’s list!

Articles
The inside story of how Apple’s new medical research platform was born by Daneila Hernandez. I know we’ve been talking a lot about ResearchKit lately, but I had to add this fantastic piece on Stephen Friend’s journey that lead him to help bring it out of Apple’s lab and onto our iPhones. Of particular interest was this sentence from a FOIA request on Apple’s meeting with the FDA in 2013:

“Apple sees mobile technology platforms as an opportunity for people to learn more about themselves. “

Your Data Is Not Your Life Story by Michael Humphrey. An interesting take on the influence of machines and algorithms on our ability to understand and tell the stories of our lives.

Data Privacy in a Wearable World by Gawain Morrison. Gawain lists five steps for companies to consider as they beocome the gatekeepers of our personal data. My favorite: “Set up an ethical body”

DJ Patil Talks Nerd to Us by Andrew Flowers. You may know DJ as the gentleman who coined the term “data scientist” or from his groundbreaking work at LinkedIn, or maybe even his new position as the deputy chief technology officer for data policy and chief data scientist at the White House. Regardless, this interview sheds some light on his new role and how he thinks about the power of data at the national level.

Wireless Sensors Help Scientists Map Staph Spread Inside Hospital by Scott Hensley. A great piece on a new research article the described a new digital epidemiology method used to track individuals and infection in a hospital. One can’t help but wonder about the future of this type of system for understanding healthcare interactions now that we have low-cost iBeacon, NFC, and RF technology embedded into our phones.

Sensored City by Creative Commons. Together with the Robert Wood Johnson Foundation and the City of Louisville, CC Science is creating an open-source project to map and visualize environmental data. So great to see this work getting out there.

Show&Tell
ShannonConners_FoodLogging Reflections on my ongoing diet and fitness project by Shannon Conners. Again Shannon wows us with her beautiful and thoughtful explanation on how tracking and visualizing her data has set her on a path to a healthy weight.

“I have now collected enough free-living data in my own n=1 study to quantify what works for me to lose weight and maintain in a healthy range for me — an understanding that largely eluded me up to this point in my life. Not surprisingly, I have converged on the same deficit strategy commonly employed in weight loss studies that treat people like caged rats, closely quantifying their intake and activity to prove that negative calorie balance is the critical factor that causes weight loss. I’m truly grateful that I didn’t need to live in a cage to learn what I have over the past few years. In many ways, learning what I have from my data has helped set me free.”

 

happiness-dashboard Tracking Joy at Work by Joe Nelson. Joe and his coworkers use Slack to communicate at work. He was wondering why sometimes things just weren’t working right so he created a tool to randomly ask himself and his coworkers how he they feel. Results are then displayed anonymously on a dashboard. So cool.

Visualizations
deardata Dear Data by Giorgia Lupi and Stefanie Posavec. Two friends track one topic each week and send each other postcards with hand-drawn visualizations based on the data. Absolutely beautiful work.

 

AirTransformed Air Transformed By Stafanie Posavec with Miriam Quick. Two wearable data objects based on open air quality data: Touching Air (a necklace) and Seeing Air (glasses).

 


Laurie Frick – American Canvas. A great interview with our friend and data artist, Laurie Frick. Make sure to watch through to the end.

Access Links
It’s Not Just the Watch: Apple Also Helping Cancer Patients
Americans Believe Personal Medical Data Should Be Openly Shared with Their Health Care Providers
What should we do about re-identification? A precautionary approach to big data privacy

From the Forum
Looking for Android Time Tracking App
Looking for a software / app to track the general health
Heart Rate and Sleep Monitor

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Ulrich Atz: Tracking 120,000 Pushups Together

In 2013 Ulrich Atz completed a unique non-digital trackign experience. When the beginning of 2014 rolled around he was convinced by a friend to start an ambitious project to complete 10,000 pushups in one year. Using his interest in habits and self-tracking he built a simple system to bring his friends into the fold so that they could all track and learn together. In this talk, presented at the London QS meetup group, he explains just how this all got started, what happened to different “types” of people throughout the year, and what he learned.

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QS15 Conference Preview: Evan Savage on Data Sense

On June 18-20 we’ll be hosting the QS15 Conference & Activate 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. We’ve made some early bird tickets available for readers of the Quantified Self blog (for a limited time):

Register here!

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Announcing the QS Access Program

QSAccessProgram

Self-knowledge through numbers. Personal meaning from personal data. These are the guiding principles of the work we do here at Quantified Self Labs. Through our editorial work, our events, and our support of a worldwide network of meetups we are focused on shaping the culture of personal data and it’s impact on our lives. We realized some time ago that impact is determined not only by data analysis skills, scientific training, or even the use of new tools and technologies (although all of these play an important role). Rather, impact is directly related to our ability to access the data we’re creating and collecting during the course of our lives.

We’re happy to announce our new QS Access Program with support from the Robert Wood Johnson Foundation. We’re working together to bring issues, ideas, and insights related to personal data access for personal and public health to the forefront of this evolving conversation. We hope you join us.

You can read the full release here. Below are two quotes from the release that embody our current and future work.

“The Robert Wood Johnson Foundation is working with many partners to build a Culture of Health in the U.S., and in that culture of health, people are attuned to the factors that influence their health and the health of their communities,” said Stephen Downs, Chief Information and Technology Officer at the Robert Wood Johnson Foundation. “The explosion of data on day-to-day life creates tremendous potential for new insights about health at both the personal and population levels. To realize this potential, people need access to their data — so they can use services that surface the connections between symptoms, behaviors and community environments and so they can choose to contribute their data to important research efforts.”

“We believe that when individuals, families, and communities are able to ask their own questions of their own data, everybody benefits,” said Gary Wolf, Director of QS Labs. “We look forward to doing our part to build a culture of health with the support of the Robert Wood Johnson Foundation, and we invite anybody who has an access story to tell to get in touch.”

If you’d like to learn more or get involved. Please contact:
Ernesto Ramirez
Program Director
Quantified Self Labs
ernesto@quantifiedself.com

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Meetups This Week

There will be five Quantified Self meetups this week. If you live in the south of England, you won’t want to miss the meetup in London. They are always excellent.

St. Louis will feature a discussion with Dr. James McCarter on fasting. McCarter will explain the science of ketosis and how to take a citizen-science approach to measuring the biological effects of fasting.

Washington, DC will have a jam-packed schedule, starting with Patrick McKnight showing his exercise and hypoxic training data from his preparation to ascend Mt. Everest. Josh Touyz and Dmitri Adler of Data Society will show the group how to get their data from the Fitbit API and analyze it. There will also be a talk from an analytical chemist on how to use blood tests to address nutritional deficiencies.

In addition to the show&tell talks in Thessaloníki­, the group will have a discussion about the possibilities of Apple’s new ResearchKit, inspired by #WhatIfResearchKit on Twitter. Background on this hashtag can be found here.

To see when the next meetup in your area is, check the full list of the over 100 QS meetup groups in the right sidebar. Don’t see one near you? Why not start your own! If you organize a QS meetup, please post pictures of your event to the Meetup website. We love seeing them.

 

Tuesday, March 17
St. Louis, Illinois

Wednesdy, March 18
Denton, Texas
London, England

Thursday, March 19
Washington, DC

Friday, March 20
Thessaloníki­, Greece

Lastly, St. Louis gets the top prize for monumental creativity with the injection of the cityscape into their logo:

global_323793892

 

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What We Are Reading

Ernesto is in sunny Austin for SXSW, so I’m filling in to gather this week’s articles and links for your reading pleasure.

Articles

Apple ResearchKit concerns, potential, analysis by MobiHealthNews. ResearchKit was a big surprise coming out of Apple’s Special Event this week. It was quite difficult to select just one representative article about the ensuing conversation, so this round-up serves nicely.

#WhatIfResearchKit: What if Research Kit actually, truly, worked… by Christopher Snider. Okay, I failed to keep to one article on ResearchKit. This post chronicles a series of Twitter conversations on the question: if ResearchKit does work, what are the possibilities?

The Electric Mood-Control Acid Test by Kevin Bullis. Thync is a sort of evolved version of a transcranial direct current stimulation (TDCS) device. A technology with a lot of potential and controversy, this article explores why the brain-enhancing effects of the TDCS only work for some people. By the way, if you are a fan of Philip K. Dick, Thync may remind you of the mood organ that was in Do Androids Dream of Electric Sheep?

Automated Learning by Nichole Dobo. Some school classrooms are experimenting with ”Blended learning”, a method of combining classroom teachers and computer-assisted lessons. A detail that stuck with me is the description of three large displays that show where each student is supposed to go that day, based on the results of the previous day’s lesson.

The Mouse Trap: Can One Lab Animal Cure Every Disease? by Daniel Engber. An in-depth how science’s predominant use of lab mice could be limiting our knowledge of disease. Of relevance to self-trackers because many models of optimal health are in part based on mouse studies.

Show&Tell

2014-Average-Sleep-Stages-by-Day-of-Week

Analyzing a Year of My Sleep Tracking Data by Bob Troia. This is a superb exploration of Bob’s sleep data from 2014 as collected by his Basis watch.

report_1

Notes on 416 Days of Treadmill Desk Usage by Neal Stephenson. The author of Snow Crash and The Cryptonomicon is a long time user of a treadmill desk, but when he began having pain in his left leg, he had to reevaluate how he used his favored tool.

Visualizations

 

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Qualities of #QuantifiedSelf by Christina Lidwin. A fascinating analysis of the #quantifiedself hashtag.

Access Links
First medical apps built with Apple’s ResearchKit won’t share data for commercial gain by Fred O’Connor
Talking Next-Gen Diabetes Tools with Dexcom Leaders by Mike Hoskins

From the Forum
Mood Tracking Methods?
Howto track laptop uptime
CCD or CCR conversion tools?
What gets measured, gets managed – Quantified Self in the workplace
Best ECG/EKG Tool for Exercise
Best iOS app to track water/coffee/alcohol intake?

This Week on QuantifiedSelf.com
QS15 Sponsor Highlight: RescueTime
Quantified Self and Apple’s ResearchKit
Better by Default: An Access Conversation with John Wilbanks
QS15 Conference Preview: Jamie Williams on Tracking My Days
Quantified Self Styles

Lastly, I’ll leave you with a lovely little comic with a message that many self-trackers can relate to.

thesecret-web
The Secret by Grant Snider

 

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Quantified Self Styles

Tokyo Quantified Self, November 2014

Tokyo Quantified Self, November 2014

Last year, over 320 Quantified Self events occurred across the globe. If spread evenly, six out of seven days of the week saw a QS meetup. This is a truly incredible amount of knowledge sharing occurring in our community.

Although many QS meetings follow our typical “show&tell” format, with three to four talks about personal tracking projects and plenty of social time, you don’t have 320 meetups occurring in a calendar year without some variation. Our organizers are a creative bunch, and they’ve tried many different formats. From informal chats and small work groups to unconference sessions and group experiments, there are meetup formats that suit the size and personality of every local Quantified Self community.

Because we are inspired by the creativity of QS organizers around the world, we’ve put together a partial catalog of Quantified Self event formats. The purpose of this list is to be a resource for meetup organizers and members, to spark new experiments and interactions. If you don’t have a Quantified Self group in your area, all is not lost. You can always start your own!

Catalog of Quantified Self formats.

How to start your own Quantified Self Show&Tell.

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QS15 Conference Preview: Jamie Williams on Tracking My Days

On June 18-20 we’ll be hosting the QS15 Conference & Activate 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. 

Jamie_bioJamie Williams has been involved with QS for a few years, giving his first show&tell talk at the Chicago QS group in Dec. 2012, and later, after moving to St. Louis, he became a co-organizer of the St. Louis QS group. In the fall of 2014 he gave a fantastic show&tell on exploring his Fitbit data. His  background in software engineering and data visualization has a deep influence on his interests in Quantified Self and self-tracking.

At the QS15 Conference Jamie will sharing his long-standing project to automate the process of continuously tracking what he’s up to during the day. He started out several years ago by building an iPhone app with a UX optimized for continuous tracking, but after using it for a week he found that manual tracking was too tedious and intrusive to be a sustainable solution.

Since then, technology has evolved to the point where it should be possible to automate this tracking using various apps, devices and sensors, whose data can be aggregated together to form a correlated timeline of how I spend my time each day.

habstatsactivities

A visualization of daily activity data taken with a prototype iPhone app Jamie built.

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)?

Jamie: I use several apps and devices, but I guess the one that seems most useful at the moment is the Fitbit Charge HR. I particularly like the automated sleep tracking.

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

Jamie: I’m looking forward to networking with other self quantifiers who are interested in activity/time tracking in particular, and hopefully finding potential avenues for collaboration. I’m also looking forward to learning about new tools that people are building.

QS: What should people come talk to you about at the conference (what are you interests and expertise)?

Jamie: I recently pivoted my career into the healthcare space with a position as a data visualization engineer at a large health system. Before that I was an iOS software engineer. One of the difficult problems in QS is how to aggregate the growing body of data streams to build a unified and coherent story that we can use to gain insight about our lives. I’d love to hear how others are approaching this.

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

Jamie: I’m really interested in seeing the next generation of biometric tracking tools, for example, blood screening. I’m also curious to learn of any projects centered around information radiators/dashboards for personal QS tracking.

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

Jamie: One of the recurring challenges in this space for any kind of tool or technique is: how to find the sweet spot balance between automated tracking and user engagement? Tracking diet is a good example: I don’t do it because it requires too much manual effort, but would love to have the data. Tracking my financial transactions, on the other hand, is completely automated, which is good, but I have almost no daily engagement with that data. The really hard problem is to find a way to automate data tracking while at the same time presenting the info to the user in a timely and compelling way that can impact their behavior.

Jamie’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. We’ve made some early bird tickets available for readers of the Quantified Self blog (for a limited time):

Register here!

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Better by Default: An Access Conversation with John Wilbanks

Photo by Joi Ito

Photo by Joi Ito

John Wilbanks is the Chief Commons Officer for Sage Bionetworks. You may not recognize John’s name or the name of his organization, but after today, you may want to commit it to memory. On March 9, 2014 Tim Cook introduced us to the idea of ResearchKit and then turned it over to Jeff Williams who described the new initiative and the five applications that were launched in collaboration with leading academic labs, advocacy groups, and research organizations. Sage Bionetworks is responsible for two of those apps, and John is responsible for leading design and development of many of the novel research tools and methods used by Sage. The following is an edited transcript of a conversation we had with John after the announcement.


Parkinson mPower App

This is Big

Think about what we’re doing in the context of it being open source. ResearchKit is going to be great for the QS community. They are perfectly suited to take advantage of ResearchKit. Let’s look at the five apps that were released today. They cover complex, but ubiquitious diseases. Plus the diseases are a great fit for the technology and sensor capabilities. But what is going to be amazing is when ResearchKit is released as open source. Anyone will have the ability to reskin these existing five apps to make novel research tools. Our Parkinson’s app might become a Huntington’s app. Our breast cancer app measures cognition really well, maybe it gets reskinned into a focused cognition tool. The app that focuses on diabetes could become a diet research app.

Large research institutions are going to jump all over this, but I’m more excited about the idea that small groups of people who have a bit of technical skill can work together to reskin the apps and turn them into longitudinal studies of 20 or 50 people. There may be five of those small groups, maybe 100. We can then work to stich those groups together and learn even more.

So the rare and chronic disease folks and the tech and QS community are involved. Now we come to everyone else. Everyone who isn’t suffering or presenting with a medical issue. We have to figure out ways to get them to participate.

We have a long tradition of creating incentives to participate. There is no reason we can’t create novel incentive methods to bring people into research. Maybe you receive a federal income tax credit. Maybe you’re allowed to enroll in long term care insurance at a reduced rate. There are a lot of ways to bring people in and that’s not touching the innate altruism of people and their curiosity. We’re already seeing this with the Precision Medicine Initiative. People want to take part, they want to engage.

Once we start getting that engagement, and we begin to see a diverse ecology of applications built on top of ResearchKit, then we’ll start to see success. It may take a bit of time. It won’t happen with this iteration. Maybe not even the second, but when we get enough devices, apps, participants, and improved interoperability between them all we’ll start to see the power of network effects.

You have to remember, there are no “killer apps” without network effects. Email wasn’t a big deal in the late 80′s because you couldn’t reach anyone outside your system. But then the web came, we connected the dots, the nodes, and then there it was, the power of the newtork.

I see QS and our current state of devices, apps, and tools being very similar to all those nerds typing away in the 80′s. They were okay with what they had because they could work with it. Then the net came and you have more control and more interefaces. That leads to the killer apps. That’s why we’re building this, for the third or fourth wave.


Share the Journey app

Everything we’re doing, the whole stack working together, is new. Consenting participants using well-designed and open-source Participant-Centered Consent toolkits. Giving participants direct access to their data. Securely hosting automatically de-identified data in the cloud using our Bridge Server. None of these have been done before at the same time.

We’re a non-profit, so we can be this icebreaker. We can take these risks and experiment and iterate and learn. No one asks us how we’re going to make money. We have a different bottom line — what is best for everyone involved? That outlook gives us the freedom to do this work.

I’m honored to have the opportunity to create a product that pushed my beliefs: participants-centric principles. If you’re a participant, then you decide. You’re in control. You can do cool stuff with the data. You can stop answering questions whenever you want. You can delete the app. We live in a world in which the politics of technology are dicteated by code and they often don’t share those ideas. To get this opportunity is amazing.

These moments don’t happen often. This is IBM going open source in the late 90s. It’s that big. I wasn’t sure I was going to be a piece of something that big. We’re trying to change culture.

In 1998 Lawrence Lessig proposed the pathetic dot theory in his book, Code and Other Laws of CyberspaceHe theorized that four forces control what we do: Law, Architecture, Social Norms, and the Market. He went futher and differentiated west coast law, which was quickly becoming dominated by software code and east coast law, what we normally think of when we think of laws.

I think up until now we’ve failed to properly take up that lever, to use software code, west coast law, to express something better. People often forget that building software means expressing an opinion. We created our apps, our tools, our systems to reflect our opinion, that participants should be at the center of research. And then we’re giving it away. That’s our position, and it’s better by default.

But, we’ve just started. The fun now is that we get to test it. I’ve always said that we can’t screw it up any worse than it already is. This isn’t the end. It’s not finished. We’re going to keep changing and learning.


John can be found online at del-fi.org and @wilbanks.

We invite you to share your data access stories, and this article with the #qsaccess hashtag and follow along on quantifiedself.com@quantifiedself and our Access Matters Medium publication.

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Quantified Self and Apple’s ResearchKit

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Apple’s announcement of ResearchKit is strong evidence that Quantified Self practices are emerging as a major influence on medical research and other forms of knowledge making.

Apple talked about how their new effort focused on opening up health research is designed to combat five main current issues:

  • Limited Participation
  • Small sample sizes limit our understanding of diseases
  • Reliance on subjective data
  • Infrequent data provide only snapshots through time
  • One-way communication from researcher to participant (and only at the end of the study, if at all)

Furthermore, the design of ResearchKit allows the  participant to decide how data is shared. Apple will not see the data. Participants are allowed to be involved in the data collection in real-time, using the data they’re collecting to understand and inform their own health improvement plans.

In light of today’s announcement we wanted to highlight some of our favorite and most powerful examples of taking the research process into one’s own hands, making their own knowledge through thoughtful data collection and reflection. We invite you watch what’s possible now, and imagine with us what could be accomplished tomorrow.

Mark Drangsholt: Deciphering My Brain Fog

Lindsay Meyer on Tracking Hearing Loss

Thomas Christiansen on Learning from 60,000 Observations

Nan Shellabarger: 26 Years of Weight Tracking

Rob Rothfarb on Tracking My Blood

Last year we gather a fantastic group of researchers, toolmakers, and science leadership at the 2014 Quantified Self Public Health Symposium to discuss how personal data can impact personal and public health. That meeting culminated in a great report that touches on many of the aspects discussed today regarding ResearchKit. We invite you to download, read, and share that report. For a more nuanced look into how ResearchKit may impact the research community, we’re highlighting four great talks from the the meeting.

Susannah Fox shares research from the Pew Internet and Life Project and describes the challenges ahead for promoting self-tracking.

Margaret McKenna explores the issues, challenges, and ideas large scale self-tracking applications have in mind when they consider working with the research community.

Jason Bobe talks about the lessons learned from involving research participants in the data ownership and discovery process.

Doug Kanter describes what he’s learned from tracking and visualizing his diabetes data.

If you’re interested in how ResearchKit will be affecting self-tracking, personal data, and access to information, research and knowledge making, then stay tuned to our Access Channel here on QuantifiedSelf.com and on Medium.

We are sure to have many great talks and sessions that focus on ResearchKit at our QS15 Conference and Actrivate Exposition. We invite you to join us.


We invite you to share your data access stories, and this article with the #qsaccess hashtag and follow along on quantifiedself.com and @quantifiedself.

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