The diversity, which is intrinsic to open data, affects intuitiveness and acceptance from the end users perspective. While the existing visualization techniques provide various ways to exploit open data in different domains, they still lack mechanisms to capture generality and flexibility across highly heterogeneous data representations that are crucial in the open data domain. We propose a novel visualization approach that exploits an entity-centric representation of open data. The key idea is that people intuitively perceive things as entities and categorize them according to their similarities and differences. The approach is supported by a UI architecture that allows aligning underlying open data described by the entities with a meaningful user experience. A preliminary user study shows the feasibility of our approach and its potential in turning the exploitation of open data catalogues into a positive user experience.