The primary tool of topological data analysis is the computation of homology groups. Computing the homology groups of a set of data requires that the data have some sort of structure. This talk will describe the process of creating a cubical complex structure for a space. Once the data is represented as a cubical set, its homology groups can be computed. The focus of this presentation is on the algorithms used in this process, including a demonstration of their use by computing homology groups of simple 2D procedural landscapes. The mathematical and programming techniques that have been employed to improve these algorithms will be discussed.