1. A non-transitory computer-readable storage medium, comprising executable instructions to: receive digital data related to a stationary dataset; and reduce an amount of data used to describe the stationary dataset by creating an index of salient features of the stationary dataset, the index created by: computing a saliency function indicating the saliency of each of a plurality of data points in the digital data, wherein computing the saliency function comprises: calculating a state probability distribution of the stationary dataset, based on the state probability distribution, grouping the digital data such that each data group has an equal probability of occurrence in the stationary dataset; and for each data group, calculating a transition distribution indicating the probability of a transition from the data group to other states; determining a set of at least one local maxima in the saliency function; and for each maximum in the set of at least one local maxima, inserting a segment of the digital data into the index, the segment corresponding to a portion of the digital data including the data point associated with the local maximum.