Designing Personal Informatics in Context: Toward Collective Well-being through Nuanced Personal Data

Personal informatics systems have the potential to support wellbeing by helping individuals better understand themselves.However, most current systems focus on quantifiable behavioral data, making it difficult to capture the implicit, contextual, and subjective aspects that underlie meaningful self-awareness.In my dissertation, I explore how self-tracking technologies can be designed to promote eudaimonic well-being through the collection and reflection of nuanced personal data embedded in users' lived experiences.I examine how personal informatics tools can be adapted to users' everyday contexts, interpersonal dynamics, and workplace environments through a series of empirical studies and system deployments.These studies investigate how individuals engage with their data, how social feedback expands self-understanding, and how organizational structures can support or constrain personal well-being efforts.This work contributes a multi-layered perspective on personal informatics that integrates intrapersonal, interpersonal, and institutional dimensions of well-being, and opens up new possibilities for designing sustainable and socially embedded self-tracking systems.