As we have hopefully succeeded to show, algebraic datatypes give designers of databases for machine learning systems a much broader set of design options, allowing them to model the problem domain more accurately without sacrificing efficiency. Future research may attempt to reveal more ways to benefit from advances in type theory so that even more invariants can be represented in data specifications while still allowing efficient model generation.