Understanding the science behind large-scale simulations and high-throughput experiments requires extracting meaning from data sets of hundreds of terabytes or more. Visualization is the most intuitive means for scientists to understand data at this scale, and the most effective way to communicate their findings with others. Even though visualization technology has matured over the past twenty years, it is still limited by the extent and scale of the data that it can be applied to, and also by the functionalities that were mostly designed for single-user, single-variable, and single-space investigation. The Institute for Ultra-Scale Visualization (IUSV), funded by the DOE SciDAC-2 program, has the mission to advance visualization technologies to enable knowledge discovery and dissemination for peta-scale applications. By working with the SciDAC application projects, Centers for Enabling Technology, and other Institutes, IUSV aims to lead the research innovation that can create new visualization capabilities needed for gleaning insights from data at petascale and beyond to solve forefront scientific problems. This paper outlines what we see as some of the biggest research challenges facing the visualization community, and how we can approach education and outreach to put successful research in the hands of scientists.