Tag Archives: qstop

Steven Dean: A Quantified Sense of Self

At our 2014 Quantified Self Europe Conference, as with all our events, we sourced all of our content from the attendees. During the lead up were delighted to have some amazing interactions with attendees Alberto Frigo and Danielle Roberts, both of whom have been engaged with long-term tracking projects. This theme of “Tracking Over Time” was nicely rounded out by our longtime friend and New York QS meetup organizer, Steven Dean. Steven has been tracking himself off and on for almost two decades. In the talk below, Steven discusses what led him to self-tracking and how he’s come to internalize data and experiences in order to create his sense of self.

Transcript
Quantified Sense of Self
by Steven Dean

Twenty years ago, I was in grad school getting an MFA. I was making a lot of objects that had very strong autobiographical component to it. Some I understood the source of. Many I did not. Continue reading

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This Week’s QS Meetups

This week there are six QS meet ups planned all over the world. Follow the links below to learn more. You can also find the full list of the over 100 QS meet ups in the right sidebar. Don’t see one near you? Why not start your own!

Monday (7/21/14)
Rio de Janeiro, Brazil
Looks like QS Rio has three great show&tell talks on tap for their meetup!

Tuesday (7/23/14)

St. Louis, Missouri
The St. Louis QS meetup group is trying something new. They’ll be screening a selection of QS show&tell talks from our vast video collection (over 700!).

Los Angeles, California
Join QS LA members for an informal “Happy Hour” to talk about QS, new tools, and interesting projects you’re working on.

Wednesday (7/23/14)

Austin, Texas
Austin QS meetup organizers, Mark and Laurie Frick are inviting the community to join them for evening of socializing and story sharing. They’ll also have a featured interview with Peter Zandan, “a Big-Data guru, investor and advisor to the Quantified-Self community. He’s noted for finding surprises in the data, and will curious to hear his take on self-tracking.” Sound like fun!

Thursday (7/24/14)

Berlin, Germany
Our friends at the Berlin QS Meetup are having their 7th show&tell Thursday evening. From the description it sounds like a fascinating talk on sleep tracking is on the agenda.

Saturday (7/26/14)

Indianapolis, Indiana 
Join the QS Indianapolis meetup group as they discuss experiences using the the popular productivity and computer use tracker, RescueTime.

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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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Peter Lewis on Meditation and Brain Function

As a long-time meditator, Peter Lewis had a suspicion that meditation could improve brain function, so he conducted a self-experiment and enlisted a few other individuals to help test his hypothesis. By using an arithmetic testing application, a timed meditation app, and an ABA research design he was find out that there was some support for meditation improving his brain function. However, other participant’s results weren’t as supportive. Watch Peter’s talk, presented at the 2013 Quantified Self Europe Conference, to learn more about his process and hear what he learned by conducting this experiment. We also invite you to read Peter’s excellent write up on Seth Robert’s blog: Journal of Personal Science: Effect of Meditation on Math Speed and the great statistical follow-up by our friend Gwern.

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QSEU14 Breakout: Measuring with Muppets

Today’s post comes to us from June Lee and Jennifer Kotler. June and Jennifer are researchers at Sesame Workshop, where they are conducting work exploring children’s media use. Below you can read their description of a breakout session they led on the topic at the 2014 Quantified Self Europe Conference. If you have ideas about measuring media use or want to continue this conversation we invite you to join the discussion in the forum.

JenKJuneL_QSEU14

Measuring with Muppets
by June Lee & Jennifer Kotler

The goal of the session was to exchange ideas for ways to measure and track children’s media use across contexts (which include physical spaces such as work vs. school, and social contexts such as with whom they are using media). An ideal device would be a wearable device that’s a “Shazam meets LENA,” which would identify the media content being used, as well as capture the conversation taking place around media use.

Currently, different technologies approximate what we would like to do. For instance, iBeacon is used in shopping malls to track and deliver messages to shoppers; smartwatches could be good for capturing audio; Bluetooth recognition could identify devices that are nearby and partly capture the social context. Different apps, however, don’t use the same system and are difficult to integrate. The main takeaway from the session is that nothing exists yet that does what we would like to do. We would need different apps and systems.

The session generated other useful ideas, such as the asking what parents would like to track in terms of media and their child, and what parents currently track (if they do). Another suggestion was to look at the rare disease or health care community, which is ahead of the curve in terms of tracking and managing child health; Human-Computer Interaction departments or Interaction Design departments at universities could be another good resource. Many agreed that we could start with simple, low-tech approaches: observations and/or manual paper recording. Or do the research in stages, using technology that does exist. In short, we needed to narrow our research questions because the tool we’re looking for does not (yet) exist.

Editor’s note: While doing some research around measurement and children we stumbled upon this great Sesame Street video. Enjoy Elmo singing about the power of measuring!

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Sky Christopherson: Personal Gold

Our friend Sky Christopherson first spoke at a Bay Area QS meetup in 2012, when he unveiled an interesting discovery about sports performance, deep sleep, and room temperature, made while he was training for a cycling competition in which he set a new world record.

(You can watch Sky’s QS show&tell talk here: The Quantified Athlete.)

Sky’s experience led him on a new journey of helping other athletes us self-tracking and personal data to obtain their best performances, culminating in a surprise silver medal for the 2012 women’s olympic track cycling team, on which he served as a training advisor. In March of this year, Sky and his wife Tamara gave another QS talk in which they told the wonderful story of how the 2012 Olympic team rode to their medal, a journey captured in the documentary, Personal Gold.

 

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QSEU14 Breakout: The Future of Behavior Change

Today’s post come to us from Lukasz Piwek. Lukasz is a behavioral science researcher at the Bristol Business School, University of West England. We were happy to welcome Lukasz, who led an well attended breakout session at the 2014 Quantified Self Europe Conference where conference attendees discussed current issues and new dimensions of behavior change. We encourage you to read his description below (which first appeared on his cyberjournal, Geek on Acid) and join the conversation in our forum

The Future of Behavior Change
by Lukasz Piwek

I gave a short talk, and moderated a breakout discussion, on the future of behaviour change in the context of quantified self approach. It was an inspiring session for me so I summarised my slides here with the discussion that followed.

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First, I highlighted that behaviour change interventions require multidisciplinary approach in order to target a broad range of behaviours related to health (e.g. healthy eating, alcohol & drug use, stress management), sustainability (e.g. travel habits change, energy saving, recycling) or education.

social2

Health interventions are good example where behaviour change can enormously benefit from smart technology. Currently we have what we call a “sick care” model: when we notice a specific symptoms of illness we share it with our GP, and we get prescription, or we’re referred for more detailed diagnosis. This classic and dominant “sick care” model focuses on relatively passive way to manage illness “after” it occurs.

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However, in the future we can envision ourselves being empowered by smart devices that track various variables in our daily life (such as heart rate, body temperature, activity levels, mood, diet). This variables will get combined in sophisticated analysis merged with our illness history and DNA screening. This continuously provides us with information about “risk factors” for illnesses, which enables us in turn to act and change our behaviour before the onset of a disease. This is what we call a real “preventive care” model of healthcare. Clearly we’re not there yet.

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The key question we discussed was: “what critical features or solutions we are missing to make a breakthrough in behaviour change interventions with quantified self approach?” I started the discussion with giving two possible answers.

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First, we lack long-term user engagement for smart wearables and self-tracking solutions. A recent study showed that 32% of users stop using wearables after 6 months, and 50% – after just over a year. Similarly, there is a high drop rate amongst smartphone apps users: 26% of apps being used only once and 74% of apps are not used more than 10 times (although discussion pointed out that we might not need long-term engagement for many interventions).

social7

Second, existing devices for self-tracking lack data validity and reliability. Proprietary closed platforms and limited access APIs make it difficult for us scientists to validate how well self-tracking devices measure what they intend to measure. This is a major problem from the perspective of methodology for behaviour change interventions in clinical context.

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In the discussion that followed my presentation, the major reoccurring theme was a lack of robust and reliable feedback provided to users/clients. We agreed that new model of feedback would incorporate such concepts as: narratives, actionable advices on specific consequences of behaviour, and personalised, rapid, relevant data visualisation.

social9

Another problem highlighted was related to psychological resistance towards smart technologies in our lives, especially in the groups that are not motivated to use wearables/self-monitoring.

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Finally, it seems clear that we’re currently focusing on “exploratory” side of quantified self, and its important we start moving towards more “explanatory” and predictive approach, like in the healthcare example described above. This requires a development of new methodology for n=1 research and creation of data bank of personal analytics. Such bank would enable better generalisation and evaluation of results for larger-scale interventions.

I’m totally on it.

If you’re interested in the intersection of Quantified Self and behavior change we invite you to join the conversation in our forum.

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Debbie Chaves: A Librarian in Numbers

Debbie Chaves is a science and research librarian at Wilfred Laurier University and was interested in understanding her job and the various demands placed on her time. Using methods she’d employed previously she set about tracking different aspects of her work. The data she gathered allowed her to advocate for new changes and policies within her library. In this video, presented at the 2014 Quantified Self Europe Conference, Debbie explains her tracking, what she found, and what she was able to accomplish.

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This Week's QS Meetups

If you’re interested in learning more about Quantified Self, meeting new and interesting people, and being inspired by unique self-tracking projects we invite you attend a local QS meetup in your area. This week there are nine QS meet ups planned all over the world. Follow the links below to learn more. You can also find the full list of the over 100 QS meet ups in the right sidebar. Don’t see one near you? Why not start your own!

Tuesday (7/15/14)
Southern Oregon Quantified Self  (Ashland, OR)

Auckland QS Show&Tell #6

Malta QS Show&Tell #2

Wednesday (7/16/14)
Dallas/Fort-Worth QS Meetup

Cincinnati QS Hangout #1

Triangle QS Meetup (Raleigh, NC)

Washington DC QS Meetup

Thursday (7/17/14)
Silicon Valley QS Meetup #12 (Mountain View, CA)

Melbourne QS Show&Tell #6

 

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What We Are Reading

Enjoy this week’s reading list. If you’d like to submit something for future What We’re Reading posts we invite you to get in touch!

Articles
Data Journalism Needs to Up Its Own Standards by Alberto Cairo. The influx of new data-based journalistic endeavors seems to grow by the day. In this great piece Alberto Cairo presents four suggestions for those practicing that art and science of data-based reporting.

Big Data Should Not be a Faith-Based Initiative by Cory Doctorow. The idea of “big data” as a miraculous fountain of new knowledge is widespread. In this article Cory Doctorow brings to light some of the major concerns about personal data and the true possibility of de-identification.

Data Privacy, Machine Learning, and the Destruction of Mysterious Humanity by John Foreman. This is a long read, but definitely worth the time. If you’re like me you’ll spend the next few hours (day?) thinking about yourself, the various companies and organizations consuming your data, and how your life may (or may not) be shaped by the information you willingly hand over.

Privacy Behaviors of Lifeloggers using Wearable Cameras [PDF] by Roberto Hoyle, Robert Templeman, Steven Armes et al. This research paper paper offers a good glimpse into the the concerns and real behaviors of people using photo lifelogging systems. This is an area we’ve previously explored (see Kitty Ireland’s great write-up about our lifelogging town hall at QSEU13) and we expect to continue discussing.

Show&Tell
Battery Life, 6mo Checkup By James Davenport. It may seem odd to have a post about tracking battery life from a laptop here in the Show&Tell section, but this is a really neat post. As part of tracking his laptop battery he also tracked his usage and led to some interesting data about his sleep. (Don’t forget to check out the post that kicked off his battery tracking.)

Bringing My Data Together by John T. Moore. John is on a journey of improving his health and being more active through self-tracking/monitoring. In this post he pulls together some of his most important data, but I also suggest reading his summary of how he got started with self-tracking.

Visualizations

carsharing
Seven Days of Carsharing by Density Design. Not exactly personal data here, but some beautiful visualizations based on one week of data from the Enjoy, a carsharing service in Milan.

aprilzero
Aprilzero by Anand Sharma. I stumbled on this website recently via the #quantifiedself feed on Twitter. The visualizations and interactivity on this personal data site are really nice.

LR_annualreports
Lee Rogers’ Annual Reports by Lee Rogers. Lee has been tracking different aspects of his life for more than three years. Since 2011 he’s put together Annual Reports detailing his personal data. You can view his 2011, 2012, and 2013 reports on his website.

From the Forum
Devising Experiments
Looking for a General QS Device
Masters Thesis: Self-Tracking Motivations
Greetings From Germany

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