Data defined by interpolation is frequently found in new applications involving geographical concepts, moving objects, and spatio-temporal data. This data leads to potentially infinite collections of items, (e.g. the elevation of any point in a map), whose definition is based on the association of a collection of samples with an interpolation function. We first argue that the manipulation of the data through direct access to the samples and interpolation functions easily leads to cumbersome or inaccurate queries. We therefore suggest hiding the samples and the interpolation function away from the logical level, and letting the system manipulate them at the physical level. We propose to model such data conceptually using infinite relations (e.g. the map with elevation yields an infinite ternary relation) which can be manipulated through standard relational query languages (e.g. SQL), with no mention of the interpolated definition. This approach is simple and establishes a clear separation between logical and physical levels.