In order for models to make relevant predictions about real ecological systems, it is helpful to have data to guide the selection of, for example, parameter values, interaction functions, and dispersal kernels. For many ecological systems, however, data is sparse. Nonetheless, these data can still lead to the development of models that give rise to theoretical predictions with real relevance. Several examples will be presented and discussed in this talk.