Introducing The Quantified Self Advisory Board!
Alexandra Carmichael
Do you need help with your self-tracking data analysis? Is there a specific problem or burning question about your experiment design that you'd love some guidance on? Gary and I are proposing an idea to help - read on for details!We've gathered an amazing Quantified Self Scientific Advisory Board to be part of our community. It's a star group of international scientists involved in data analysis, data visualization, and self-experimentation. In alphabetical order, they are:
- Alex Bangs, Human Predictive Biosimulation, Entelos
- Gordon Bell, MyLifeBits, author of Total Recall, Microsoft Research
- Jeff Heer, Collaborative Data Visualization and Flare/Prefuse, Stanford
- Gary King, Quantitative Social Science and n=1 experiments, Harvard
- Teresa Lunt, Director of Computer Science Lab, PARC
- Seth Roberts, Self-Experimentation guru, author of Shangri-La Diet, Berkeley and Beijing
- Neil Rubens, Data Mining, University of Electro-Communications, Tokyo
The experiment we'd like to do is to encourage Quantified Self members to formulate questions about the personal data that they are trying to work with. Post them as comments or send them to me. We will make sure the questions are interesting and at least partially answerable, pass them along to the appropriate Advisor, and publish the questions and responses here on the Quantified Self blog, as a way to get discussion going and add value to everyone involved.
So let us know what you think, and start asking questions!
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I’d like to run an n=1 experiment to normal variations of my current lifestyle and behaviors that allow me to make evidence-based decisions to increase my energy level. My objective is to quantify the relative influence that each of these factors have on my energy level: 1. Sleep (times, times awaken) 2. Exercise (time, intensity) 3. Diet (time, general comments/tags) 4. Medications & Supplements (time each is taken)
Two questions: 1. What tool or set of tools… a. will minimize the burden of data collection? b. have integrated analysis tools to minimize custom coding effort in order to make meaning of the results? (e.g. Keas, The Carrot, Medhelp, Fitbit, Zeo) 2. What metric is best for self-assessing mood and energy level? (e.g. I liked the 2-D mood graph that Margie showed at the meetup)
Thanks!
Jeremy
When do I have have the most creative thoughts … when I am reading, when I am thinking, or when I do intermittent periods of reading and thinking?
Re: Jeremy
I have spent the last two years building a spreadsheet-based tool just as you describe. Currently I run it through the handy google docs form utility which makes the data collection much easier. I collect about 30 data points about myself a couple of times each day and have done for many months now, resulting in a massive amount of data. Re: Alexandra I have spent the last three months trying to teach myself advanced statistics and data mining practices in order to try and make sense of the data and find useful correlations. Unfortunately, this is not my full time job and so progress is painfully slow. Any help that could be provided by your experts would be greatly appreciated. I am currently running simple correlative coefficients and pearson formulas, but have identified many gaps in these approaches. Would love to discuss this further with people who have a better grasp of the math. I am so pleased to have stumbled upon this website - exactly the community I’ve been looking to connect with. I would be willing to make public examples of how my personal metrics tool works if you’re interested. Kind regards, Bard