When the data source produces a low-probability value (i.e., when a low-probability event occurs), the event carries more "information" than when the data source produces a high-probability value. This notion of "information" is formally represented by Shannon's self-information quantity, and is also sometimes interpreted as "surprisal". The amount of information conveyed by each individual event then becomes a random variable whose expected value is the information entropy.