The skyline operator has been proposed to bridge the gap between traditional and multimedia database systems by finding the optimal objects according to the notion of Pareto dominance. According to the notion of Pareto dominance an object dominates another if it is better in one attribute and equal in all others. Skyline sets end up being pretty large because of the "curse of dimensionality". Many skyline reduction algorithms have been proposed to choose "interesting" objects from skyline sets in order to reduce their size. The purpose of this master thesis is to propose a new way of using reduction algorithms, that is to summarize datasets. A framework is proposed for interactive query refinement that will give users an overview of their query results provided by a skyline reduction algorithm. On the grounds of summarizing datasets different reduction algorithms will be compared against each other and a new novel reduction algorithm will be proposed that will hopefully summarize better query results.