Hyperspectral imaging instruments are producing large volumes of data that pose a challenge for data analysis. Hylatis is a NASA funded project to build interactive hyperspectral image analysis tools backed by cloud resources. Hylatis is built on the LaTiS software package which implements a Functional Data Model (FDM) that builds on the relational data model and relational algebra used by many database systems. The FDM captures the functional relationship between independent and dependent variables that are inherent in scientific data. By representing data as Functions, we can take advantage of mathematical constructs such as function evaluation and composition in addition to other dataset operations that define a functional algebra. This talk will re-introduce the Functional Data Model (first presented to the SEA in 2012) and demonstrate how using this abstraction enables innovative techniques for manipulating scientific datasets.