Tag Archives: dataviz
David de Souza: I’ve been recording 35 of the most important areas of my life – and using Google Spreadsheets to create a personal dashboard that tracks my progress.
Tracking 35 metrics might seem like a daunting task. Everything from quantum theory to tracking-based anxiety shows that the mere act of observing affects the observed. Automating personal data collection might help us stress less, collect more, and (hopefully) be more accurate.
David has managed to create a streamlined workflow allowing him to record everything from sleep, weight and food intake to productivity, yoga and meditation. At QS17, David is going to share this dashboard and the correlations he’s drawn between diverse aspects of his behavior. He says his dashboard has done ”wonders to keep me accountable, and more importantly, to help me notice when I have fallen off the horse, allowing me to keep on track with my goals.” For those of us (all of us) looking to optimize our workflows and understand our habits, this is definitely a talk to see.
Join us at QS Amsterdam June 17-18, and if you haven’t already, check out our latest program. See you there!
Could a personalized comic strip change the way you see your data? At QS17, Andreas Schreiber will share what may be the first Quantified Self comic strips. Well, maybe the first actually based on personal data. Andreas is excited to share this project because techniques like this could make self-tracking easier and more fun. Andreas is a founder of PyData Cologne and the Cologne QS Meetup, and an advocate of open source code to help ensure the reproducibility of scientific research. He has previously given a Show&Tell talk on recovering from a stroke and has since founded a company which creates apps to help others do the same.
QS conferences are an amazing place to share ideas shaping the future of wearable devices, precision medicine, and personal understanding. Join us at QS17, June 17-18, in Amsterdam.
We’re back again with another round of visualizations from our QS15 Conference and Expo attendees. In today’s batch you’ll see a variety of representations of different tracking projects, from tracking biometrics while watching a movie to running distance over nearly 13 years. Enjoy!
Name: Bob Troia
Description: I tracked my heart rate, HRV, and galvanic skin response while watching the movie Interstellar (in IMAX!), then plotted the data to understand how my body reacted during the 3+ hour movie. (Check Bob’s blog post about this data here!)
Tools: Polar H7 chest strap, SweeBeat Life app (iPhone), Basis B1 band, Excel.
Name: Tahl Milburn
Description: This shows sleep over a week. The overall height of the bar is the time in bed. The part above the baseline is actual sleep whereas the part below 0 is restless sleep or awakening during the night. The line above the bars is the goal number of hours. The bar itself is green is all okay, turns yellow if overall duration is short or awakened too much. Red is even worse.
Tools: Google Charts with data from Fitbit.
Name: Tahl Milburn
Description: This is a very simple but powerful chart. T his is a “Life Gauge” which show how much of my statistical life has already been used. The ultimate age is based on the consensus estimate from several sources. Note the yellow and red markings indicating that one might be running out of life soon.
Tools: Google Charts for the graph itself. Several sources for computing the ultimate age.
Name: Julie Price
Description: My running miles per week plus marathons since 2002.
Tools: Tracked running miles using various methods and recorded both on paper and, in the past few years, on a Google sheet. Summarized & graphed in Excel before manually adding in marathons.
Name: Allan Caeg
Description: ”How much did you win today?” is one of the most important questions I ask myself every day. This pre-sleep question constantly gets me to reflect on what I did with my free will, inspiring me to ensure that I’d make the most out of every day.
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!