Ablating, i.e. removing, part of a model and observing the impact this has on performance is a common method for verifying that the part in question is useful. If performance doesn't go down, then the part is useless and should be removed. Carrying this method over to datasets, it should become common practice to perform dataset ablations, as well, for example: