BIOS 513: Data Visualization with Applications to the Life Sciences

3 credits

Fridays, 09:00 – 11:30, Fall 2026

Rosenau 228

Gillings School of Global Public Health

The University of North Carolina at Chapel Hill

Course Overview

Most individuals receive little formal training in producing effective data visualizations, applying them to novel problems, and interpreting them in practice. This is unfortunate, as data visualization is one of the most powerful approaches to communicate the story hidden among the data. The goal of this course is to describe visualization methodologies to aid in the interpretation and communication of data from applications in clinical trials and other life science topics. Participants will gain hands-on experience in producing, evaluating, and interpreting numerous data visualizations using data from the scientific literature.

To be accessible to most students, this course will utilize JMP and the Graph Builder platform to interactively build data visualizations without the need to write code. However, students may use any software to complete assignments if they adhere to the graphical principles discussed in class and produce work independently.

Learning Objectives

1.     Describe the transition from traditional methods of data summary to visual approaches

2.     Understand the relationship of the data format to the visualization

3.     Assess the strengths and limitations of various graphical techniques

4.     Interpret and communicate the “data story” through numerous examples   

Additional Details

This is a portfolio-based course. Students produce a portfolio of data visualizations encompassing a variety of endpoints and graphical types. Half of the data visualizations will be produced from instructor-provided scientific articles and/or data sources, with the remainder produced from student-identified sources. In addition to the portfolio, students present their strongest data visualizations to the class. Justifying graphical choices and interpreting plots in the context of the scientific problem are key to success.