Managing Information for Personal Goals

1. Managing Information for Personal Goals CIDR’13 Gong Show Alan Fekete (University of Sydney) Ongoing work with Judy Kay, Bob Kummerfeld, Debjanee Barua (Uni of Sydney))

2. Persuasive Computing • Rapidly growing set of application domains • Health goals • Learning goals • Personal/professional development goals • Sensors: devices and system-based agents • Eg Fitbit, wireless bathroom scales, keyboard activity monitor, Learning Management Platform • Displays: devices and agents • Context-specific adaptation • How to nudge effectively depends on personal style, distance to goal, current focus of attention

3. Distinctive features for data • Contested ownership • Platform seeks to monetize • Subject seeks control and privacy • Legislation may govern this • Wide and deep inferences • Across sources, for a subject • Across subjects, for a platform • Varying access control • People’s concern varies by feature, age of data, and between people!

4. Initial idea: Data Lifecycle • Working data • Active long-term • Inactive long-term • Deleted/expired • Retracted

5. Initial idea: data model • Valid time • System store time • Vector clock (timestamp per source) • Tradeoff between complete provenance and management overhead

6. Where to? • Build architecture for exchange of data, derived data and models • UI design for control and access • Case studies • Usability evaluation