Clusters appear in various guises in data analysis, but they are what you think they are, namely groups of things "in proximity" determined by parameters that vary. The parameters are often distance or time, or both. The trick, in mathematical models, is to describe the meaning of proximity.

This talk will describe the persistence approach to the description and analysis of clusters, with a method that involves graphs.