In this report, we introduce a flexible and scalable volume visualization system for visual browsing of spatially and temporally large datasets in distributed computing environments. Our framework leverages advances in high-speed networks for access to shared scalable computation, data storage and graphics. In particular, we assume commodity off the shelf graphics hardware for both, rendering and data processing. We describe the implementation and integration of the various pipelines within our visualization framework and present examples of applications in seismology and biological tomography. The quintessential goal of this research is to create an adaptive visualization framework that is cognizant of the constraints in the various pipelines and accordingly, optimizes the visualization process dynamically.