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Methods to Test Visual Attention Online
Published on: February 19, 2015
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A systematic method for surveying data visualizations and a resulting genomic epidemiology visualization typology:
Anamaria Crisan1, Jennifer L Gardy2,3, Tamara Munzner1
1Department of Computer Science, University of British Columbia, Vancouver, Canada.
Bioinformatics (Oxford, England)
|September 27, 2018
Summary
We developed a method to systematically organize data visualizations for genomic epidemiology. This creates an explorable design space, aiding researchers in understanding and choosing effective visualization tools.
Area of Science:
- Genomic Epidemiology
- Data Visualization
- Bioinformatics
Background:
- Data visualization is crucial for genomic and healthcare data analysis.
- A systematic approach is needed to organize visualization design choices.
- Researchers need guidance to distinguish effective from ineffective visualizations.
Purpose of the Study:
- To develop a method for systematically surveying and organizing data visualizations.
- To construct an explorable visualization design space.
- To create a typology for visualizations in genomic epidemiology.
Main Methods:
- Systematic analysis of scientific articles using text and image data.
- Development of a method to explore visualization design space along 'why' and 'how' axes.
- Application to infectious disease genomic epidemiology research.
Main Results:
- Creation of the Genomic Epidemiology Visualization Typology (GEViT).
- GEViT describes visualization construction through chart types, combinations, and enhancements.
- An online gallery was implemented to explore the visualization design space.
Conclusions:
- The developed method and GEViT offer implications for visualization design.
- Researchers can better develop and utilize data visualization tools.
- The method is extensible to other research domains for creating visualization design spaces.
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