Tag Archives: personal analytics
One of the important factors that influence your happiness and quality of life, in my opinion, are your personal values and whether you live according to your value priorities. Modern psychologists define values as “guiding principles of your life”, and, depending on the method, values can be measured in terms of absolute or relevant importance. In September and
October August, I tracked my personal values in order to assess their stability and to see how they interact with other variables in my everyday life. In this and the following post, I will share some interesting insights I was able to get from that data.
If you live in New York, you probably already know that NY Quantified Self community has held its quarterly meeting this Thursday, November 15. I have been attending NYQS meetups regularly for quite some time now, but this time I was especially thrilled because I helped to organize it. With overwhelming turnaround, engaging Show&Tell sessions, creative presentations, and community interaction and networking afterwards, the meetup, as always, exceeded my expectations. In this post, I will sum up the presentations that made this event so informative, inspirational and thought-provoking.
One of the self-tracking projects that I always wanted to do was to determine the impact of sleep, diet and exercise regimen on my mental and cognitive abilities. So last month, I turned to the app store to look for mobile tools that could help me to measure and track my cognitive performance. After three weeks of searching and testing, I finally found three apps that I can use with confidence in my self-tracking experiments.
As you may know, I have been searching for a short yet reliable metric to track my happiness levels. In the past three months, I have tested three different methods, and the most recent tool, a short version of Ryff’s subjective well-being scales looks very promising. Hopefully, I will start using these questions to track happiness on a daily and/or weekly basis, and will be sharing with you soon some insights based on that data. In this post, however, I would like to review another great tool that enables you not only track happiness and life satisfaction at more granular levels and on a long-term basis, but also provides a diagnostic feedback on how you could improve your well being.
After becoming fascinated by the Quantified Self movement a couple of years ago, I have immersed myself in self-tracking, and have been using this blog to document my personal experiences and thoughts, and review different tools and measures that I tried. When I started this blog, the scope of topics was limited to physical and mental health and fitness, but this list has been growing since then. The objective of the Measured Me project has evolved and become more ambitious than ever. I am now searching for the best ways to measure and track as many aspects of my everyday life as possible. But what is it exactly that I am trying to achieve? What is the ultimate goal of this ongoing experiment? In this post, I will discuss the new raison d’être behind the Measured Me experiment – theory of life optimization.
When I made my September self-tracking data available for download, I thought I should include some sort of disclaimer. Not to limit access to data, but rather protect myself from potential liabilities associated with use, analysis and interpretation of my data by other parties. I turned to the Internet to find out how this disclaimer should look like, but to no avail: most of the discussions around Quantified-Self data so far have focused on data portability and privacy issues. I then turned to Twitter, Facebook, and Quantified-Self forum. My post on Quantified Self forum actually resulted in small but somewhat heated discussion, so I thought I should elaborate more on this issue in a separate post. So today I would like share my thoughts on some potential legal pitfalls associated with publishing your quantified-self research and data, and how they could be avoided by including a disclaimer.
If you downloaded my September data (you can do it here, absolutely free!), you probably noticed that the research agenda behind data collection that month was focusing primarily on diet, exercising (#fitsperiment!), and sleep. I finally found time to look closer at some of that data, and in this post, will share some interesting results of my sleep data analysis.
A couple of weeks ago a small wellness startup from UK contacted me with request to share some of my self-tracking data. They are working on a presentation for potential investors, and are planning to include insights from my data as an example of how self-tracking could be used in public health programs. I was more than happy to oblige, not because of the vanity, but because it serves a great cause. It is for the same reason I also just approved unlimited access to my OpenPaths data to a couple of public research projects. And I am not going to stop there. After thorough considerations, I decided that from now on, I will be making some of my self-tracking data available for download, along with the detailed description of the variables that I tracked. My September data is now public and up for grabs, along with the data dictionary (both packed into a Zip file).
I was rereading my last post, and realized that I omitted one more potential way to monetize self-tracking apps: distributing them among health and fitness practitioners. The idea of prescribed apps has been entertained by medical professionals for a while now. Think doctors that prescribe an app along with the pills; patient then uses the app to track symptoms before and during the treatment. Think personal fitness trainers that offer the app to their clients so they could track their progress in losing weight or gaining muscles. The app in this case is a tool that will provide an objective unbiased feedback to both sides. What do you think?
In my previous post, I started describing the quantified self app that I would have built myself, if I had access to necessary skills or resources. Originally, these notes were intended for software developers and enterpreneurs who contacted me after reading my post about my search for a good tracking app. After putting the notes together, I thought that it would be only fair if I shared them publically, so other developers, and Quantified Self practitioners like myself, could have a word in further discussion, should it ever ensue. This last portion of the notes will focus on analytical features of the app, data portability, and potential methods for monetization.