Resource Aware Visualisation Environment (RAVE)
RAVE Public Beta
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Visualisation is an effective way of interpreting the contents of very large numerical data sets, and extracting scientific insights from them. Visualisation transforms data into graphical representations, and exploits the high bandwidth of the human visual system and the brain's ability to find patterns, trends, and anomalies, and to make inferences from them. The power of visualisation is further augmented if it is used within a collaborative environment that allows several people at different locations to interact with the same data. This can be done effectively within an immersive environment that creates a shared virtual space.
The RAVE project has developed a collaborative visualization environment that scales from immersive platforms, such as CAVEs and ImmersaDesks, to non-immersive PCs and workstations, and even to PDAs or any other network-enabled display. Because of the diverse capabilities of the display platforms the environment is "resource-aware" in the sense that the platform where the rendering is done and the graphical representation sent to a display client will be determined by factors such as the capabilities of the client and the network bandwidth. If a client cannot locally render the scene, it will be rendered remotely on a RAVE Render Server, with the available network bandwidth taken into account to select an appropriate level of compression to ensure a consistent framerate. If the client can render locally (sufficient memory and graphics card resource), the dataset itself may be downsampled to produce an acceptable frame rate at the client. If the client cannot produce a reasonable frame rate, then it will "fall back" to using a Render Service to provide a rendered image of the data. Note that an identical user interface is provided in either mode, so the user does not have to be aware of which technique was selected.
RAVE has so far been tested on SGI IRIX, SGI Altix, Sun Solaris, Microsoft Windows XP, Linux (IA64, AMD64, i386 and embedded). The current implementation uses Web services with Java to provide data services (to host and distribute data) and render services (to support devices that have insufficient resources to render the dataset locally). Multiple simultaneous clients are supported, ranging from Java (using Java3D to render) to C++/QTopia (PDA client making use of render services to render). Services are discovered via the WeSC UDDI server.