Tag Archives: visualizations

QS Gallery: Bob Troia

This entry comes to us from Bob Troia. Bob runs the excellent Quantified Bob blog where he explores self-tracking and experimentation. Make sure to check out this post where he explains how he created this great visualization of his movement data.

Here’s a cool visualization of approximately 1 month of my location data in and around New York City using Moves and a Processing sketch Nicholas Felton put together. Yellow lines are walking (you’ll see the hot spots where I walk my dog or around my office, blue are cycling (usually to/from the soccer field), and gray are subways/car/taxi. Pretty neat! It shows that I am very much a creature of habit (or I walk the same routes all the time to conserve willpower! :)

Tools: Moves; Moves Mapper

We invite you to take part in this project as we share our favorite personal data visualizations.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

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The QS Gallery: Personal Data, Personal Meaning

On October 10th and 11th we held our fifth Quantified Self conference. These conferences have become a wonderful part of our ongoing work to share how people get personal meaning from their personal data. QS Show&Tells are the cornerstone of the program. In these short talks, we get to hear what you did, how you did it, and what you learned.

Visualizations of personal data are often important in a QS Show&Tell, so this year we made a simple request of all our conference attendees: send us your favorite personal data visualization and tell us what it means to you. Within a few hours we started receiving amazing images. We posted them at the conference and created some great conversation around making meaning through visualization. But a conference only lasts a few days, so we decided to start publishing them here, along with the same request to you. 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

Be on the lookout as we begin this journey of sharing our personal meaning making through visualization. The images below are just a preview. Over the coming days, we’ll be putting each of the over 50 QS visualizations into its own post, along with a description and some links.

Thank you to everybody who came to the conference this year and shared their amazing work. See you Amsterdam in May!

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What We Are Reading

We hope you like these links, articles, and ideas that we’ve enjoyed this week.

From Gary Wolf

Apple Gives Massive Nod to Wearable Tech in New iOS7 Update: This analysis of iOS7 changes for wearable technologies argues that the iPhone’s future as a QS hub matters more than the much hyped and hypothetical Apple Watch.

Drawing Dynamic Visualizations” [video] – Many clues here in this Bret Victor talk about the future of understanding our personal data. Be sure to check out the supplemental material on his website.

The Scientific Life: A Moral History of a Late Modern Vocation, by Steven Shapin: I’m finding this book very influential in shaping my reaction to some of the pious statements about “real science” that I encounter in discussions of the Quantified Self movement. Here’s an interview with Shapin that includes a link for the book.

From Ernesto Ramirez

Quantifying the body: monitoring and measuring health in the age of mHealth technologies: A thoughtful research article by Deborah Lupton exploring to sociocultural implications on self-tracking on health and identity.

A Timeline of Smartphone-enabled Health Devices by Mobihealthnews: A great look back at the how far the field of mHealth has come since 2009.

Lifeloggers by Memoto [video]: This short documentary explores the world of lifelogging through various interviews with experts such as Gordon Bell and Steve Mann.

A Personal API by Naveen Selvadurai: Naveen, co-founder of Foursquare, has started to open up his data in the form of an “personal API.” He’s challenged developers and the broader QS community to see what they can do with this data. Right now his API allows access to sleep, steps, weight, fuel (Nike Fuelband), and places.

We’ve also noticed two open challenges that might appeal to the QS community:

The Economist-Lumina Foundation Quantified Work Challenge: The Economist and the Lumina Foundation are asking for your thoughts on what “potential objective inputs or data and potential methods of collecting and reporting that information that organizations could use to build a personalized “skills tracker” for individual employees.”

Chart.js Personal Dashboard Challenge: Use the open source chart.js javascript visualization library to create your own charts and graphs based on your personal data.

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Talking Data With Your Doc : The Patient

Data.

Health.

Communication.

In our daily lives, we are keenly aware of the power of each of these individual concepts. However taken together, their influence on our wellbeing, to borrow a phrase from my friend Karen Herzog, “our wholeness”, is exponentially influential. So why do they seem to rarely coalesce during our conversations, discussions, and interactions with the individuals and institutions tasked with tracking, diagnosing, and treating the cracks and fissures in our wholeness?

This is the first in a three-part series about the data we produce about our health and how we communicate that information to the medical system, specifically the providers of care. We’re starting from the perspective of the patient because we’ve all been there. Whether it was a routine check up or a 3AM visit to the emergency room, we’ve all had to relay information to a medical provider about out health. So what happens when we’ve collected, stored, and tried to understand our own health information in preparation for those visits?

Our guide today for the patient perspective of health data communication is Katie McCurdy. Katie is a user experience designer and researcher living and working in New York. She is also living with Myasthenia gravis, an autoimmune disease that causes muscle weakness  in voluntary muscles. Like many individuals with  autoimmune diseases, Katie spend a lot of time communicating and working with the medical system. These visits, although regular, were a point of contention between Katieand the individuals entrusted with her care. So when she was going to see a new physician for the first time she decided to apply her interaction design knowledge and skill. She’s talked about this on her blog and on the e-patients.net blog so I’ll let here words speak for themselves:

As I was getting ready to see a new doctor, I realized that the best way to tell my story would be to create a medical “life story” timeline that reflected:

  • The course of my autoimmune disease
  • Severity of my gastrointestinal problems
  • Key moments in time when I started and stopped certain medications or took antibiotics
  • Any significant dietary changes

I sketched out the two timelines (autoimmune and gastrointestinal) separately, and then created them electronically using Adobe Illustrator. (I’m an interaction designer by day, so fortunately I had the skills/know-how to create a somewhat legible artifact.) I used a peach color to represent gastrointestinal wellness/symptoms, and a blue color for Myasthenia Gravis.

Katie's Medical Timeline

Katie was kind enough to answer a few questions and we’re grateful to be able to share her responses here with you today.

QS: Why visualize? Do you think doctors are more receptive to the visual translation of data rather than the raw numbers that are commonly associated with health data?

KM: For me it’s about creating a representation of my history and my health that can be communicated most efficiently. I believe in the power of visualization to help tell stories that wouldn’t be possible with raw data alone. Knowing I would be ‘on the spot’ during my doctor visit put the pressure on to make something that would help me tell my story as succinctly as possible. Also…because I was not tracking my data (it’s all from memory) I didn’t have the raw data to share anyway!

QS: I’ve been thinking about the doc-patient relationship a lot lately. It seems the walls of authority are crumbling as we speak and we’re moving from a “You do this” or “You listen to me” type of authoritative approach to medicine to more conversational. How do you see data and visualizations helping to start and possibly support those conversations.

KM: I see it as, like you said, changing the dynamics of the relationship so that the patient is more of a partner in care. By tracking data, the patient can provide a more refined and nuanced picture of what is really going on with them. By visualizing that data, the patient is helping the doctor absorb the information more painlessly. The patient is providing contextual information about his or her OWN situation that compliments the doctor’s past experience, expertise, and test results.

QS: You mention in your post that the reception from patients and caregivers has been really positive, how would do we help make it a positive and rewarding experience for the providers as well?

KM: I think that giving patients tools to create simple, clean, and attractive visualizations could help make the experience better for doctors. If doctors are presented with high-quality visualizations that tell a coherent story, it may make office visits more efficient. Imagine if the doctor could work with the patient and suggest a type of graph or visualization that would be most helpful.

QS: What tips or advice would you give to someone who is taking their data to their doc for the first time?

KM: I suggest using the data as a storytelling tool. Bring a printed artifact or something on a tablet to refer to, and point out the highlights as you talk about what’s been going on with you. Don’t be disappointed if they don’t comment on your beautiful data and all of the work you put into it. Ask if there is anything you can do to to make the data more legible/easy to understand for the doc.

QS: You mention that self-tracking has given you better insights into your own health and that you’re even trying some self-experimentation like a no-carb diet. How do you think self-tracking and data communication with physicians can support patient-initiated health experimentation?

KM: Ah, I think self-tracking and visualization can help increase patient compliance! My low-carb diet was actually prescribed by my doctor. When I saw on the timeline that my diet changes were strongly correlated with my gastro symptoms improving, it was very reinforcing of my diet behavior. I mentioned antibiotics in my post. Now, if I even think of asking for antibiotics, all I can see in my mind is the number of antibiotics I took as my stomach issues got worse and worse. That is a big change in my outlook that resulted from internalizing the data I was seeing on the timeline.

QS: Who are your design/data viz heros? Anyone who really inspires you in your health visualizations?

KM: I have a few data viz heros! Jer Thorpe, of the new york times, makes beautiful interactive data visualizations and is one of the best speakers I have ever seen. Nicholas Felton, of Feltron and now a designer at Facebook, is a compulsive self-tracker who releases a gorgeous printed yearly report. I love Mortiz Stefaner’s work as well. I am really inspired by the natural world and the work of 19th century plant and wildlife documentor Ernst Haekel. I am also inspired by the awesome patients I’ve met and the folks on e-patients.net who remind me that patients need to be their own advocates.

We also have some questions from Susannah Fox, who was kind enough contribute her thoughts and insights to this piece:

SF: Would Katie care to comment on that from her own experience? That is, is it only recently that she has both found the right tools and that her own clinicians are interested? Had she attempted something earlier, with pencil & paper? What has made the difference?

KM: I never did anything before this apart from bringing notes to my doctor visits – things to remember to say. I literally had a realization one day at work and wrote an email to my personal account with the subject: ‘very important idea.’  :)  I think the idea had to incubate for a few years before it bubbled up.last fall. 

My goal is to keep pursuing this idea and work toward creating a tool for patients so they can at least assemble their own health timeline, and perhaps even track their data more regularly. I am holding interviews with patients, patient caregivers (or parents), and people who are active self-trackers; if you are interested in donating about 30 minutes of your time, email me at kathryn.mccurdy at gmail.com.

Again, this is part one in a three-part series on the data centric conversation we engage in with the medical community. Look for our next part with insights from Dr. Eric Topol and Dr. Larry Chu next Thursday. If you have questions of comments feel free to discuss on Facebook, Twitter, and here in our comments.

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Numbers from Around the Web: Round 4

Karsten W. is on an amazing journey towards understanding his personal finances. Thankfully for us he’s been writing about his methods and what he’s learned along the way over at his blog: FactBased. Let’s dive in!

Step 1. Track 

Karsten decided to use twitter to track his expenses and supplement that data with his normal bank statements. Not simply satisfied with this seemingly simple step, he went a bit further and compared his twitter entries to the data from his bank to see how well he was able to self-track:

KarstenW_twitterBank

Kartsen's Expense Tracking: Tweet vs Bank Comparison

Step 2: Classify

Having compiled his full year of monetary tracking, Karsten then looked to how to better understand where his money was going by classifying his spending. He looked into classification schemes and settled on using the United Nations Classification of Individual Consumption According to Purpose. Why?

It is made by people who have thought more about consumption classification than I ever will.

Again, he did some amazing number crunching and visualized his entire year.

KarstenW_ExpenseClassification

Inkblot chart of expenditures by classification

Step 3. Compare

So Kartsen has his expenditure data and he has it classified according to a simple schema. What’s next? Why not compare it to what is typical for someone like him! Karsten did some digging and found the German Federal Statistics office completes surveys of consumption and income every five years. He pulled the data that most closely reflected his income level and created a neat comparison:

Personal expenditures vs typical expenditures

I found this series of blog posts to be fascinating. For one, Karsten wasn’t just satisfied with tracking his finances for a full year. He went above and beyond and did some personal data analysis using some really neat tools and methods. I highly suggest you read his posts on tracking, classification, and comparison. Not only are the posts interesting, they also include short “how-to” write ups if you want to implement his analytical and visualization methods using R (an free statistical program). Keep up the great work Karsten!

Every few weeks be on the lookout for new posts profiling interesting individuals and their data. If you have an interesting story or link to share leave a comment or contact the author here.

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