Contextualizing sensor data: integrating user voice in data-driven design

Data-driven design increasingly relies on sensor data, yet these thin measurements often lack the experiential context needed to explain why events occur or what users feel and need. This limits their value for human-centred design. Passive and active contextualisation are introduced to describe how meaning is produced through inference and user participation. A real-world case study using See.Sense cycling data from Melbourne shows how combining thin and thick data produces more situated understanding and actionable design insight.