Big data is getting personal. People around the globe are monitoring everything from their health, sleep patterns, sex and even toilet habits with articulate detail, aided by mobile technology. Whether users track behavior actively by entering data or passively via sensors and apps, the quantified self (QS) movement has grown to become a global phenomenon, where impassioned users seek context from their big data identities.
Moreover, with services like Saga and Open Sen.se, users can combine multiple streams of data to create insights that inspire broader behavior change than by analyzing a single trait. This reflects a mixed approach design (MAD) research methodology that purposely blends quantitative and qualitative factors in a framework where numbers are driven by nuance. The science of happiness, for example, is now a serious study for business, as organizations combine insights of the head and heart to create environments where workers feel their efforts foster meaningful change.
However it’s studied, the desire to understand monitored behavior has reached a fever pitch, and the QS movement is attempting to meaningfully interpret our daily data.
The Power of Passivity
“We’re moving towards a time when the ability to track and understand data is deeply woven into our daily lives,” says Ernesto Ramirez, community organizer for Quantified Self, the eponymous organization created byKevin Kelly of Wired and Gary Wolf. “Sensors are becoming cheaper and connectivity is more ubiquitous by the day.”
This ever-present nature of data availability will become even more powerful when the general public begins to use apps that require little ongoing attention or input. Passive data collection is especially relevant in the healthcare industry, for example.
“The data quantified self provides is not a replacement of any measurement to date — we haven’t had this type of measurement to date,” says Halle Tecco, co-founder and CEO of Rockhealth, the first seed accelerator for digital health startups. “Patients live very cautiously before trips to doctors, and this causes more trips to doctors. It’s better if physicians can get a more comprehensive view of people’s ongoing health.”
Tecco highlights the importance of passive monitoring. For instance, a mobile app can continuously measure glucose levels or other factors like heart rate over time. Spikes in those readings could immediately trigger a doctor, even remotely. “We can save money and improve outcomes by having data collection embedded in our everyday lives,” she adds.