Although our ability to collect personal information has increased dramatically through personal informatics tools such as personal digital tracking technologies for step counts, location, and more, minimal attention has been paid to designing tools to generate actionable insight from data. Self-reflection is important to generate these insights; however, without scaffolding to support the process, it is often ineffective. In this thesis, I introduce and explore shared reflection – the reciprocal process of reflecting on others’ data and having others reflect on one’s own data – as a means to bootstrap the reflection process. I synthesize literature on personal informatics and social learning theories, design and conduct a six-week personal data collection study, and evaluate the results. Shared reflection appears to show promise; however, users value privacy and control over their personal data when sharing in a social context. Finally, the potential application of shared reflection to new personal informatics tools is explored.