Date of Award

Fall 9-2015

Embargo Period

4-21-2016

Degree Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Human-Computer Interaction Institute

Advisor(s)

Jason I. Hong

Second Advisor

John Zimmerman

Abstract

Personal data is everywhere. The widespread adoption of the Internet, fueled by the proliferation of smartphones and data plans, has resulted in an amazing amount of digital information about each individual. Social interactions (e.g. email, SMS, phone, Skype, Facebook), planning and coordination (e.g. calendars, TripIt, Basecamp, online to do lists), entertainment (e.g. YouTube, iTunes, Netflix, Spotify), and commerce (e.g. online banking, credit card purchases, Amazon, Zappos, eBay) all generate personal data. This data holds promise for a breadth of new service opportunities to improve people’s lives through deep personalization, through tools to manage aspects of their personal wellbeing, and through services that support identity construction. However, there is a broad gap between this vision of leveraging personal data to benefit individuals and the state of personal data today. This thesis proposes unified personal data as a new framing for engaging with personal data. Through this framing, it synthesizes previous research on personal data and describes a generalized framework for developing applications that depend on personal data, exposing current challenges and issues. Next, it defines a set of design goals to improve the state of personal data systems today. Finally, it contributes Phenom, a software service designed to address the challenges of developing applications that rely on personal data.

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