Gene regulatory network models are a major area of study in systems and computational biology and the construction of network models is among the most important problems in these disciplines. The critical epistemological issue concerns validation. Validity can be approached from two different perspectives (i) given a hypothesized network model, its scientific validity relates to the ability to make predictions from the model that can be checked against experimental observations, and (ii) the validity of a network inference procedure must be evaluated relative to its ability to infer a network from sample points generated by the network. This article examines both perspectives in the framework of a distance function between two networks. It considers some of the obstacles to validation and provides examples of both validation paradigms.