Cuttlefish: Color Mapping for Dynamic Multi-Scale Visualizations.

Visualizations of hierarchical data can often be explored interactively. For example, in geographic visualization, there are continents, which can be subdivided into countries, states, counties and cities. Similarly, in models of viruses or bacteria at the highest level are the compartments, and below that are macromolecules, secondary structures (such as α-helices), amino-acids, and on the finest level atoms. Distinguishing between items can be assisted through the use of color at all levels. However, currently, there are no hierarchical and adaptive color mapping techniques for very large multi-scale visualizations that can be explored interactively. We present a novel, multi-scale, color-mapping technique for adaptively adjusting the color scheme to the current view and scale. Color is treated as a resource and is smoothly redistributed. The distribution adjusts to the scale of the currently observed detail and maximizes the color range utilization given current viewing requirements. Thus, we ensure that the user is able to distinguish items on any level, even if the color is not constant for a particular feature. The coloring technique is demonstrated for a political map and a mesoscale structural model of HIV. The technique has been tested by users with expertise in structural biology and was overall well received.

A Jini service to reconstruct tomographic data.

Distributed computing that uses dynamic networks will change the way we work and communicate thanks to the interaction of devices and services, that are automatically added and removed from the network as needed. The Jini technology, which is built atop the Java programming language, provides a homogenous view of the network and extends the ability of code to migrate in Java. This software design model simplifies the configuration and access to hardware devices and software services in a network. Thus, it becomes possible to execute new services without pre-installing software on client machines. This new programming paradigm is especially important in medical applications, where the reliable transmission of information is essential. This paper demonstrates how single photon emission computerized tomography data can be iteratively reconstructed using a Jini service.