Data Face explores how data and mathematical information can be used to represent an individual. The resulting images are geometric portraits that are not initially obviously portraits. In my work, I try to explore the three Ps that are consistent in my practice. These Ps are perception, perspective and process. I explore these through data visualisation and data-based portraits. This highlights the power of information, personal data and how it is presented as well as the ease of data manipulation. I have invented a machine that maps facial features by plotting significant common points on the X, Y and Z axis of the subject’s head. From these measurements, I am able to generate individual geometric data-based portraits that are unique to the subject. Data Face highlights the similarities between individuals as well as the subtle differences e.g. age, gender and race. The portraits are numerically accurate and give information about the shape and features of an individual, but they do not give anything away about the person. What does taking away age, sex, and gender tell us about people’s prejudices? Data Face also tackles the larger current question on personal data and how it is used.