1. A method comprising: statistically sampling, at a server, a set of animation data for an element in an animation to obtain a common context, the common context being a subset of a plurality of frames of the set of animation data; segmenting, at the server, the plurality of frames of the set of animation data into a first subset and a second subset; sending, from the server to a first client, a first data set corresponding to the first subset; sending, from the server to a second client, a second data set corresponding to the second subset; receiving, from the first client at the server, a first error that results from a first comparison in the first data set of the first subset of output of a data-driven model for the animation, which utilizes at least a subset of the common context, with output of a computational model for the animation, the computational model having a first set of logic, the data-driven model having a second set of logic that has less logic than the first set of logic; and receiving, from the second client at the server, a second error that results from a second comparison in the second data set of the second subset of output of the data-driven model for the animation, which utilizes at least the subset of the common context, with output of the computational model for the animation.