BMI 6340 Health Information Visualization and Visual Analytics

3 semester credit hours
Lecture contact hours: 2; Lab contact hours: 3
Web-based and classroom instruction
Lab Fee: $30
Department Focus Area: Health Data Science and Artificial Intelligence

This course introduces the basics of information visualization, which is the use of interactive visual representations of data to amplify human cognition. Properly constructed visualizations allow us to analyze data by exploring it from different perspectives and using the power of our visual system to quickly reveal patterns and relationships. This course uses practical, hands-on examples and exercises to teach the theory and application of information visualization for health data. The class emphasizes visual analysis of time-series data, ranking and part-to-whole relations, deviations, distributions, correlations, multivariate, and geographic data. You will also learn how to combine multiple visualizations into interactive dashboards and how to use Tableau, a state-of-the-art information visualization tool to produce and deliver visualizations and dashboards quickly and easily.

Upon successfully finishing this course, you will:

• Identify and explain when to use non-visual data displays (such as tables) and when to use visual displays (such as graphs).
• Identify and explain user characteristics (information needs and features of the human perceptual system), theories, and guidelines that support the construction of effective information visualizations for visual analytics.
• Identify and describe why some visualizations are effective for a given task whereas others are not.
• Use an instructor-selected visualization tool (such as Tableau) to connect to healthcare data and create effective information visualizations, including dashboards.
• Select the most appropriate kinds of information visualizations based on user information needs and characteristics of the data.
• Describe and create effective information visualizations for visually displaying and analyzing time-series data, ranking and part-to-whole relations, deviations, distributions, correlations, and multivariate data.
• Create dashboards of multiple, interactive and interlinked visualizations to meet specific user needs.