AbstractsCommunication

Information Experience Design: The Path to Emotional Data Visualization for the Masses

by Yuping Qin




Institution: Savannah College of Art and Design
Department:
Year: 2016
Keywords: Thesis (M.F.A.)  – Graphic Design; Savannah College of Art and Design  – Department of Graphic Design
Posted: 02/05/2017
Record ID: 2064284
Full text PDF: http://ecollections.scad.edu/iii/cpro/DigitalItemViewPage.external?sp=1003246


Abstract

'While technology has improved the capability and efficiency of data visualization, it also makes the representation of the information overly reductive, abstract, identical, less human, and overly dependent on screenbased media. As a result, this overabundance of information becomes of little value and cannot have a profound influence on the audience. It is therefore important to make data visualization more emotional and human, without sacrificing its accuracy, clarity, and efficiency. This thesis proposes a concept of information experience design to realize emotional data visualization. The thesis especially focuses on the field of data visualization to disseminate knowledge to the masses. The proposed concept of information experience design is based on the integration of data visualization and experience design. The thesis will research data visualization, emotion, and experience design to study how emotion and experience can affect people’s cognition, learning, decision making, and behaviors in a realworld environment. This thesis examines and proposes a different way to build emotional connections between data and its intended audiences through experiences, without sacrificing the accuracy, the clarity, and efficiency of the visualization. The purpose of this thesis is to explore a new way to practice data visualization that can maximize the value and influence of the information that the data visualization presents to the audience.' Keywords: data visualization, emotion, emotional data visualization, experience design, information experience design, knowledge data visualization Advisors/Committee Members: CHAIR: DiGioia, Joseph, Kwon, Sohee, Belic, Zoran.