Background: The increasing sophistication of self-tracking technologies allows individuals to generate significant quantities of timely and accurate data about their lifestyle, biology, and environment, which can be used to support health interventions and measure outcomes. However, such user-generated data is often not treated with the sensitivity of other medical data, with data stored and processed by vendors with commercial motivations, such as enabling targeted advertising and making inferences from linked data. As the sensors and applications which enable these technologies continue to become more sophisticated, the privacy implications may become more severe. Methods for systematically identifying and