Over the past thirty years, the visualization community has developed theories and models to explain visualization as a technology that augments human cognition by enabling the efficient, accurate, and timely discovery of meaningful information in data. Along the way, practitioners have also debated theories and practices for visualization evaluation: How do we generate durable, reliable evidence that a visualization is effective? Interestingly, there is still no consensus in the visualization research community how to evaluate visualization methods. The goal of this chapter is to rise awareness of still open issues in the visualization evaluation and to discuss appropriate evaluations suitable for different visualization approaches. This includes user studies and best practices to conduct them but also other approaches for suitable evaluation of visualization. The chapter is structured as a moderated dialog of two visualization experts.