The Quantified Self is a thriving community of enthusiasts tracking their own behaviour and activities. Here's why they matter.
Public discourse on data seems to veer between two extremes: the lucrative potential of Big Data to provide new insights and efficiencies vs. dystopian threats to privacy and the individual. Unfortunately, these polarizing stories neglect to address how we consumers can benefit from our own personal data. This subtlety is not lost on the Quantified Self community of scientists, hackers, developers and hobbyists, http://quantifiedself.com. With a shared belief in the potential of data to help individuals know themselves better, these followers are creating large personal data sets and deriving correlations and meaningful patterns in the results.
People track for a lot of different reasons: some have a problem to solve, while others want to encourage a new habit. Still others do it because they can: technology has made it easy, so why not keep the data if it might be useful someday?
Tracking to the Masses
Indeed, finding and using tools to self-track (without a lot of work) has never been easier. Wearable sensors like the Fitbit, Fuelband and Jawbone Up are bringing self-tracking to the masses, while apps like Moves use GPS and accelerometer data to estimate activity levels.
From APIs to open data, the agenda from the latest Quantified Self conference tackled some of the toughest questions concerning the technical standards and norms emerging in our data-driven world. No other community is as personally invested in what’s personally at stake. Self-quantifiers are sensitive to the fact that commercial tools and apps require users to accept their terms and relinquish control over the data in the process, and some refuse to use apps that do not allow data export.
The discussions around data handling seem to be having an impact; Jawbone, for example, has recently opened up its data ecosystem. And the more these tools can talk to each other, the more valuable they become (see story on Tictrac below).
My Data, Myself
So what’s all this measurement measuring? I am a self-tracker and it helps me understand my body. I can track calories, exercise, weight and water intake, among other things. When I can see the result of my choices over time, it’s easier to make a healthier choice and understand its impact. Somehow, the goal of “staying hydrated” is more concrete when I can break it down into numbers: fill favourite water bottle 3 times = 64 oz. a day.
Not everything I track is about the numbers, of course. Data can also be an autobiographical tool. I check in using Foursquare, I log my reading habits on Goodreads, I tweet, I journal. When I look back on all those traces, I have a better sense of where I’ve been, where I am today and where I’m going. By aggregating social media traces, apps like Timehop and Momento are making it even easier for me to see my “day-in-history” story.
My data means something to me because I understand its context. A record Fitbit day of 35,000 logged steps is more than just an outlier: it’s a day spent wandering around Venice. I’m building stories around my data.
We’re also leaving traces of where we’ve been in the digital world. My browser and search history, along with cookies, drives the advertising I see online. The difference is that muck of this data lacks context.
Judging by my tech blog reading history alone, a behavioural targeter might statistically assume that I’m a 30-year-old male. And as soon as I change my marital status on Facebook, I’m assumed to be in the baby market. These rough assumptions don’t always match up with my intentions. As a consumer, I don’t have many ways to correct these faulty assumptions, which messes with the personalization and targeting potential of Big Data.
Indeed, marketers should attempt to give consumers more control, not less. When my own story doesn’t match the story I’m being sold, we’ve missed an opportunity for truly meaningful personalization. Giving me the opportunity to match my story with my data helps achieve both personal and commercial objectives.
Data may be all around us, but taking control of it has been a challenge. Tictrac, for example, is a personal data dashboard that lets you aggregate all your activities in one place, including your calendar, physical activities, email activity and even calorie consumption. It then presents the data in engaging infographics and emails.
Are you interested in how your coffee consumption affects your blood pressure? Or how your workload impacts your sleep? The correlations you can establish are endless. Does the music you listen to change the speed at which you run? Combine your activity training tracker and your Facebook/Spotify account to produce the result.
Founded in 2010 and based in London, Tictrac is free to use. The company generates revenues by building white label tracking and advice services for brands such as Red Bull and health insurance providers.