Traditionally, skyline and ranking queries have been treated separately as alternative ways of discovering interesting data in potentially large datasets. While ranking queries adopt a specific scoring function to rank tuples, skyline queries return the set of non-dominated tuples and are independent of attribute scales and scoring functions. Ranking queries are thus less general, but cheaper to compute and widely used. In this paper, we integrate these two approaches under the unifying framework of restricted skylines by applying the notion of dominance to a set of scoring functions of interest.