Recent developments in occlusion management for 3D environments often involve the use of dynamic transparency, or "virtual X-ray vision", to promote target discovery and access in complex 3D worlds. However, there are many different approaches to achieving this effect and their actual utility for the user has yet to be evaluated. Furthermore, the introduction of semitransparent surfaces adds additional visual complexity that may actually have a negative impact on task performance. In this paper, we report on an empirical user study investigating these human aspects of dynamic transparency. Our implementation of the technique is an image-space algorithm built using modern programmable shaders to achieve real-time performance and visually pleasing results. Results from the user study indicate that dynamic transparency provides superior performance for perceptual tasks in terms of both efficiency and correctness. Subjective ratings are also firmly in favor of the method.

Motion constraints providing guidance for 3D navigation have recently been suggested as a way of offloading some of the cognitive effort of traversing complex 3D environments on a computer. We present findings from an evaluation of the benefits of this practice where users achieved significantly better results in memory recall and performance when given access to such a guidance method. The study was conducted on both standard desktop computers with mouse and keyboard, as well as on an immersive CAVE system. Interestingly, our results also show that the improvements were more dramatic for desktop users than for CAVE users, even outperforming the latter. Furthermore, the study indicates that allowing the users to retain local control over the navigation on the desktop platform helps them in familiarizing themselves with the 3D world.

While an important factor in depth perception, the occlusion effect in 3D environments also has a detrimental impact on tasks involving discovery, access, and spatial relation of objects in a 3D visualization. A number of interactive techniques have been developed in recent years to directly or indirectly deal with this problem using a wide range of different approaches. In this paper, we build on previous work on mapping out the problem space of 3D occlusion by defining a taxonomy of the design space of occlusion management techniques in an effort to formalize a common terminology and theoretical framework for this class of interactions. We classify a total of 50 different techniques for occlusion management using our taxonomy and then go on to analyze the results, deriving a set of five orthogonal design patterns for effective reduction of 3D occlusion. We also discuss the "gaps" in the design space, areas of the taxonomy not yet populated with existing techniques, and use these to suggest future research directions into occlusion management.

Supporting visual analytics of multiple large-scale multidimensional datasets requires a high degree of interactivity and user control beyond the conventional challenges of visualizing such datasets. We present the DataMeadow, a visual canvas providing rich interaction for constructing visual queries using graphical set representations called DataRoses. A DataRose is essentially a starplot of selected columns in a dataset displayed as multivariate visualizations with dynamic query sliders integrated into each axis. The purpose of the DataMeadow is to allow users to create advanced visual queries by iteratively selecting and filtering into the multidimensional data. Furthermore, the canvas provides a clear history of the analysis that can be annotated to facilitate dissemination of analytical results to stakeholders. A powerful direct manipulation interface allows for selection, filtering, and creation of sets, subsets, and data dependencies. We have evaluated our system using a qualitative expert review involving two visualization researchers. Results from this review are favorable for the new method.

Navigation in complex and large-scale 3D virtual environments has been shown to be a difficult task, imposing a high cognitive load on the user. In this paper, we present a comprehensive method for assisting users in exploring and understanding such 3D worlds. The method consists of two distinct phases: an off-line computation step deriving a grand tour using the world geometry and any semantic target information as input, and an on-line interactive navigation step providing guided exploration and improved spatial perception

Supporting visual analytics of multiple large-scale multidimensional datasets requires a high degree of interactivity and user control beyond the conventional challenges of visualizing such datasets. We present the DataMeadow, a visual canvas providing rich interaction for constructing visual queries using graphical set representations called DataRoses. A DataRose is essentially a starplot of selected columns in a dataset displayed as multivariate visualizations with dynamic query sliders integrated into each axis. The purpose of the DataMeadow is to allow users to create advanced visual queries by iteratively selecting and filtering into the multidimensional data. Furthermore, the canvas provides a clear history of the analysis that can be annotated to facilitate dissemination of analytical results to outsiders. Towards this end, the DataMeadow has a direct manipulation interface for selection, filtering, and creation of sets, subsets, and data dependencies using both simple and complex mouse gestures. We have evaluated our system using a qualitative expert review involving two researchers working in the area. Results from this review are favorable for our new method.

Recent developments in occlusion management for 3D environments often involve the use of dynamic transparency, or virtual "X-ray vision", to promote target discovery and access in complex 3D worlds. However, there are many different approaches to achieving this effect and their actual utility for the user has yet to be evaluated. Furthermore, the introduction of semi-transparent surfaces adds additional visual complexity that may actually have a negative impact on task performance. In this paper, we report on an empirical user study comparing dynamic transparency to standard viewpoint controls. Our implementation of the technique is an image-space algorithm built using modern programmable shaders to achieve real-time performance and visually pleasing results. Results from the user study indicate that dynamic transparency is superior for perceptual tasks in terms of both efficiency and correctness.

We present TrustNeighborhoods, a security trust visualization for situational awareness on the Internet aimed at novice and intermediate users of a distributed file sharing system. The TrustNeighborhoods technique uses the metaphor of a multi-layered city or fortress to intuitively represent trust as a simple geographic relation. The visualization uses a radial space-filling layout; there is a 2D mode for editing and configuration, as well as a 3D mode for exploration and overview. In addition, the 3D mode supports a simple animated "fly-to" command that is intended to show the user the context and trust of a particular document by zooming in on the document and its immediate neighborhood in the 3D city. The visualization is intended for integration into an existing desktop environment, connecting

While an important factor in depth perception, the occlusion effect in 3D environments also has a detrimental impact on tasks involving discovery, access, and spatial relation of objects in a 3D visualization. A number of interactive techniques have been developed in recent years to directly or indirectly deal with this problem using a wide range of different approaches. In this paper, we build on previous work on mapping out the problem space of 3D occlusion by defining a taxonomy of the design space of occlusion management techniques in an effort to formalize a common terminology and theoretical framework for this class of interactions. We classify a total of 25 different techniques for occlusion management using our taxonomy and then go on to analyze the results, deriving a set of five orthogonal design patterns for effective reduction of 3D occlusion. We also discuss the "gaps" in the design space, areas of the taxonomy not yet populated with existing techniques, and use these to suggest future research directions into occlusion management.

Inter-object occlusion is inherent to 3D environments and is one of the challenges of using 3D instead of 2D computer graphics for visualization. Based on an analysis of this effect, we present an interaction technique for view-projection animation that reduces inter-object occlusion in 3D environments without modifying the geometrical properties of the objects themselves. The technique allows for smooth on-demand animation between parallel and perspective projection modes as well as online manipulation of view parameters, enabling the user to quickly and easily adapt the view to reduce occlusion. A user study indicates that the technique provides many of the occlusion reduction benefits of traditional camera movement, but without the need to actually change the viewpoint. We have also implemented a prototype of the technique in the Blender 3D modeler.

We present CiteWiz, an extensible framework for visualization of scientific citation networks. The system is based on a taxonomy of citation database usage for researchers, and provides a timeline visualization for overviews and an influence visualization for detailed views. The timeline displays the general chronology and importance of authors and articles in a citation database, whereas the influence visualization is implemented using the Growing Polygons technique, suitably modified to the context of browsing citation data. Using the latter technique, hierarchies of articles with potentially very long citation chains can be graphically represented. The visualization is augmented with mechanisms for parent-child visualization and suitable interaction techniques for interacting with the view hierarchy and the individual articles in the dataset. We also provide an interactive concept map for keywords and co-authorship using a basic force-directed graph layout scheme. A formal user study indicates that CiteWiz is significantly more efficient than traditional database interfaces for high-level analysis tasks relating to influence and overviews, and equally efficient for low-level tasks such as finding a paper and correlating bibliographical data.

Inter-object occlusion is inherent to 3D environments and is one of the challenges of using 3D instead of 2D computer graphics for information visualization. In this paper, we examine this occlusion problem by building a theoretical framework of its causes and components. As a result of this analysis, we present an interaction technique for view projection animation that reduces inter-object occlusion in 3D environments without modifying the geometrical properties of the objects themselves. The technique provides smooth on-demand animation between parallel and perspective projection modes as well as online manipulation of view parameters, allowing the user to quickly and easily adapt the view to avoid occlusion. A user study indicates that the technique significantly improves object discovery over normal perspective views. We have also implemented a prototype of the technique in the Blender 3D modeller.

Is 3D audio an interesting technology for displaying navigational information in an indoor environment? This study found no significant differences between map- and 3D audio navigation. The user tasks tested involved finding objects in a real office environment. In order to conduct the study, a custom-made 3D audio system was built based on a public-domain HRTF-library to playback 3D sound beacons through a pair of earphones. Our results indicate that 3D audio is indeed a qualified candidate for navigation systems, and may be especially suitable for environments or individuals where vision is obstructed, insufficient, or unavailable. The study also suggests that special cues should be added to the pure spatial information to emphasize important information.

Causality visualization is an important tool for many scientific domains that involve complex interactions between multiple entities (examples include parallel and distributed systems in computer science). However, traditional visualization techniques such as Hasse diagrams are not well-suited to large system executions, and users often have difficulties answering even basic questions using them, or have to spend inordinate amounts of time to do so. In this paper we present the Growing Squares and Growing Polygons methods, two sibling visualization techniques that were designed to solve this problem by providing efficient 2D causality visualization through the use of color, texture, and animation. Both techniques have abandoned the traditional linear timeline and instead map the time parameter to the size of geometrical primitives representing the processes; in the Growing Squares case, each process is a color-coded square that receives color influences from other process squares as messages reach it; in the Growing Polygons case, each process is instead an n-sided polygon consisting of triangular sectors showing color-coded influences from the other processes. We have performed user studies of both techniques, comparing them with Hasse diagrams, and they have been shown to be significantly more efficient than old techniques, both in terms of objective performance as well as the subjective opinion of the test subjects (the Growing Squares technique is, however, only significantly more efficient for small

We present Growing Polygons, a novel visualization technique for the graphical representation of causal relations and information flow in a system of interacting processes. Using this method, individual processes are displayed as partitioned polygons with color-coded segments showing dependencies to other processes. The entire visualization is also animated to communicate the dynamic execution of the system to the user. The results from a comparative user study of the method show that the Growing Polygons technique is significantly more efficient than the traditional Hasse diagram visualization for analysis tasks related to deducing information flow in a system for both small and large executions. Furthermore, our findings indicate that the correctness when solving causality tasks is significantly improved using our method. In addition, the subjective ratings of the users rank the method as superior in all regards, including usability, efficiency, and enjoyability.

We present a novel information visualization technique for the graphical representation of causal relations, that is based on the metaphor of color pools spreading over time on a piece of paper. Messages between processes in the system affect the colors of their respective pool, making it possible to quickly see the influences each process has received. This technique, called Growing Squares, has been evaluated in a comparative user study and shown to be significantly faster and more efficient for sparse data sets than the traditional Hasse diagram visualization. Growing Squares were also more efficient for large data sets, but not significantly so. Test subjects clearly favored Growing Squares over old methods, naming the new technique easier, more efficient, and much more enjoyable to use.