Human-Data Interaction for Self-Monitoring

Established: September 28, 2012

Empowering people to improve their lives by fully leveraging the data about themselves


In recent years, we have witnessed rapid advancements in consumer health technologies. People are also increasingly tracking personal health data outside the clinic using wearable sensing devices and mobile health applications. For example, we have observed the rise of the Quantified Self (QS) movement, which aims to improve health, maximize work performance, and find new life experiences through self-tracking. While people can acquire a large amount of data such as health, work, and other activities, most people including Quantified-Selfers fail to fully understand and make use of their data.

We note the three distinct yet interrelated phases where people interact with their data–data collection, data analysis, and data sharing. We study ways to promote positive behavior change through design and evaluation of various technologies across the three phases. We aim to support the entire process such that people can assess, be aware of, and self-reflect on their behaviors as well as share meaningful insights about themselves.


Portrait of Eun Kyoung Choe

Eun Kyoung Choe

Assistant Professor

University of Maryland, College Park