Genomic Epidemiology Visualization Typology (GEViT)

A Method of Systematically Surveying Data Visualizations Using the Analysis of Text and Images

Lead: Tamara Munzner

diagram of data

The GEViT project is a collaboration between PhD student Anamaria Crisan, DFP faculty member (CS) Tamara Munzner, and Jennifer Gardy (faculty, UBC School of Population and Public Health & Senior Scientist, BC Centre for Disease Control), in the health care domain. We have developed a method that systematically surveys data visualizations using the analysis of both text and images. Our method supports the construction of a visualization design space that is explorable along two axes: why the visualization was created and how it was constructed. We applied our method to a corpus of scientific research articles from infectious disease genomic epidemiology and derived a Genomic Epidemiology Visualization Typology (GEViT) that describes how visualizations were created from a series of chart types, combinations, and enhancements. We have also implemented an online gallery that allows others to explore our resulting design space of visualizations. This paper is now published.

Link to Paper

View Demo of GEViT

A systematic method for surveying data visualizations and a resulting genomic epidemiology visualization typology: GEViT 

Anamaria Crisan Jennifer L Gardy Tamara Munzner

Bioinformatics, bty832,