Biological aggregations such as bird flocks, fish schools, and insect swarms are striking examples of collective motion, and serve as the inspiration for algorithms in robotics, computer science, applied mathematics, and other fields. Aggregations give rise to massive amounts of data, for instance, the position and velocity of each group member at each moment in time during a field observation or numerical simulation. Interpreting this data to characterize the group’s dynamics can be a challenge. To this end, I apply topological data analysis to the model of Vicsek et al. (1995), related to biological aggregations and active matter. The analysis identifies dynamical events that traditional methods do not and guides exploration of the data. This talk assumes no prior knowledge of topology. In the last few minutes of this talk, we will completely switch gears and discuss a few results related to gender representation in STEM fields.