A Visualization Language

In 1967, visualization theorist Jacques Bertin suggested applying seven dimensional representations to construct visualization. He further suggested that understanding the rules of construction would enable us to choose the visual variables which would lead to the most efficient representation. To use signs to depict certain meanings, he said: “all the participants come to agree on certain meanings expressed by certain signs and agree to discuss them no further.”

Bertin’s inspiration has borne fruit in this century, as visualization techniques have enabled scientists to see the invisibles, with increasing accuracy and improved decision-making process. However, there is limited study on the method of visual construction. For a given dataset, there may be an infinite number of encodings to explain it to domain scientists, but some can be more effective and efficient than others. In this talk, I will examine some, including the solution to the diffusion magnetic resonance imaging, a complex dense spatial structure studied in the past decade. I will also discuss how novel design of visual construction will unify the interface design to allow more efficient query of large complex bat fight motion datasets. My idea is to place the discovery in the lens of design making use of flexible displays to enable fluid workflow to facilitate scientists' quest for new knowledge.

Speaker Bio: Jian Chen is an Assistant Professor in the Department of Computer Science and Electrical Engineering at the University of Maryland, Baltimore County. She did a postdoctoral study in Computer Science at Brown University after receiving a Ph.D. degree in Computer Science from Virginia Tech. Her research interests include visualization, user interface, and design in general.

Presentation Slides: PDF

Note: Visitors from outside NIST must contact Cathy Graham; (301) 975-3800; at least 24 hours in advance.