Visual analytics is the science of analytical reasoning facilitated by interactive visual interfaces. It has grown out of and is strongly related to information visualization. Visual analytic tools assist analysts in detecting the expected and discovering the unexpected from complex, noisy, incomplete, heterogeneous, and sometimes deliberately deceptive data. VR/AR research has claimed for years to provide the potential for more effective environments to understand and explore information spaces. This would seem to make VR technology a natural for application to visual analytics. However, visual analytics is focused on the analytical process not the tools and technology. As such, any new methods, techniques, and technologies need to show benefit to analysts working on real problems. Additionally, the majority of visual analytics research funding is not focused on disruptive physical interface technologies. Generally speaking, new technologies and techniques for visual analytics need to function within the current analytical environment. The purpose of this panel is to introduce the domain of visual analytics to the audience and explore how and where VR/AR research can be adapted for use in visual analytics. The panelists have been selected based on topic areas of research that have potential for near term insertion or impact on visual analytics. This panel will focus on the hard issues of defining what it will take to get VR technology introduced into the visual analytics research funding stream.

Continued advances in display hardware, computing power, networking, and rendering algorithms have all converged to dramatically improve large high-resolution display capabilities. We present a survey on prior research with large high-resolution displays. In the hardware configurations section we examine systems including multi-monitor workstations, reconfigurable projector arrays, and others. Rendering and the data pipeline are addressed with an overview of current technologies. We discuss many applications for large high-resolution displays such as automotive design, scientific visualization, control centers, and others. Quantifying the effects of large high-resolution displays on human performance and other aspects is important as we look toward future advances in display technology and how it is applied in different situations. Interacting with these displays brings a different set of challenges for HCI professionals, so an overview of some of this work is provided. Finally, we present our view of the top ten greatest challenges in large highresolution displays.

In the late 90’s the emergence of high performance 3D commodity graphics cards opened the way to use PC clusters for high performance Virtual Reality (VR) applications. Today PC clusters are broadly used to drive multi projector immersive environments. In this paper, we survey the different approaches that have been developed to use PC clusters for VR applications. We review the most common software tools that enable to take advantage of the power of clusters. We also discuss some new trends.

We present the design and implementation of InfoStar, an adaptive visual analytics platform for mobile devices such as PDAs, laptops, Tablet PCs and mobile phones. InfoStar extends the reach of visual analytics technology beyond the traditional desktop paradigm to provide ubiquitous access to interactive visualizations of information spaces. These visualizations are critical in addressing the knowledge needs of human agents operating in the field, in areas as diverse as business, homeland security, law enforcement, protective services, emergency medical services and scientific discovery. We describe an initial real world deployment of this technology, in which the InfoStar platform has been used to offer mobile access to scheduling and venue information to conference attendees at Supercomputing 2004.

STARLIGHT is an example of a new class of information system expressly designed around visualization-oriented user-interface. Incorporating more traditional information storage and retrieval technologies into its design, the STARLIGHT system also enables the integrated use of multiple, concurrent visualization techniques to support comparison of content and interrelationship information levels of abstraction simultaneously. This powerful new form of information analysis eases cognitive workloads by providing a visual context for the information under study. Originally developed for intelligence analysis applications, the STARLIGHT software is intended to support the rapid, concurrent analysis of complex multimedia information, including structured and unstructured text, geographic information, and digital imagery. The system uses novel 3-D visualization techniques that interactively generate easily understandable representations of explicit and implicit relationships contained in information collections of various types. This paper describes the general theory behind our approach, and the design and features of a Windows NT-based operational system.