Data-Driven Interfaces: Portraying the Internal and External Identity

Kat Take, MFA ’10

thesis abstract

Identity is a fluid concept that changes through time. Identity as a whole is constituted of external and internal identity. External identity is determined by how others perceive us and our public images through our behaviors and appearances. Internal identity is constructed by our past experiences which create emotional responses that affect how we evaluate ourselves, and the ideal image that we want to portray. They continuously co-influence one another through time; therefore defining identity is a continuous, rediscovering process.

I believe there are patterns in our lives. We reflect on happy, disappointing, or unknown situations based on our past experiences. We learn about ourselves through the process of self-reflection; however, this reflective process is difficult when we are trying to gather information through our mind’s thoughts alone. How can dynamic media be a tool to help us understand ourselves better? This thesis proposes to use dynamic media to create data-driven interfaces that allow users to transform unique personal data into information to discover patterns in their lives.

My case studies demonstrate how external identity and internal identity can be visualized as patterns from information that have been collected form personal data; and that they are cyclically affecting each other from two different aspects in life: relationships and fashion. Case study I, Love Analytics, addresses how our internal identity evolves as we accumulate information through interpretation of our experiences and our external identity. Case study II, Style Me, examines external identity and its changes through our outward manifestation of internal identity and others’ perception of our external identity. Both case studies explore, through the use of dynamic media, the idea that identity is a cyclical, ongoing process of self-discovery.