  Technological advances for measuring or simulating volume data have led to
large data sizes in many research areas such as biology, medicine, physics, and
geoscience. Here, large data can refer to individual data sets with high
spatial and/or temporal resolution as well as collections of data sets in the
sense of cohorts or ensembles. Therefore, general-purpose and customizable
volume visualization and processing systems have to provide out-of-core
mechanisms that allow for handling and analyzing such data. Voreen is an
open-source rapid-prototyping framework that was originally designed to quickly
create custom visualization applications for volumetric imaging data using the
meanwhile quite common data flow graph paradigm. In recent years, Voreen has
been used in various interdisciplinary research projects with an increasing
demand for large data processing capabilities without relying on cluster
compute resources. In its latest release, Voreen has thus been extended by
out-of-core techniques for processing and visualization of volume data with
very high spatial resolution as well as collections of volume data sets
including spatio-temporal multi-field simulation ensembles. In this paper we
compare state-of-the-art volume processing and visualization systems and
conclude that Voreen is the first system combining out-of-core processing and
rendering capabilities for large volume data on consumer hardware with features
important for interdisciplinary research. We describe how Voreen achieves these
goals and show-case its use, performance, and capability to support
interdisciplinary research by presenting typical workflows within two large
volume data case studies.

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