IEEE VIS Publication Dataset

This paper describes the adaptation and evaluation of existing nested-surface visualization techniques for the problem of displaying intersecting surfaces. For this work, we collaborated with a neurosurgeon who is comparing multiple tumor segmentations with the goal of increasing the segmentation accuracy and reliability. A second collaborator, a physicist, aims to validate geometric models of specimens against atomic-force microscope images of actual specimens. These collaborators are interested in comparing both surface shape and inter-surface distances. Many commonly employed techniques for visually comparing multiple surfaces (side-by-side, wireframe, colormaps, uniform translucence) do not simultaneously convey inter-surface distance and the shapes of two or more surfaces. This paper describes a simple geometric partitioning of intersecting surfaces that enables the application of existing nested-surface techniques, such as texture-modulated translucent rendering of exteriors, to a broader range of visualization problems. Three user studies investigate the performance of existing techniques and a new shadow-casting glyph technique. The results of the first user study show that texture glyphs on partitioned, intersecting surfaces can convey inter-surface distance better than directly mapping distance to a red-gray-blue color scale on a single surface. The results of the second study show similar results for conveying local surface orientation. The results of the third user study show that adding cast shadows to texture glyphs can increase the understanding of inter-surface distance in static images, but can be overpowered by the shape cues from a simple rocking motion.

The study of stress and strains in soils and structures (solids) help us gain a better understanding of events such as failure of bridges, dams and buildings, or accumulated stresses and strains in geological subduction zones that could trigger earthquakes and subsequently tsunamis. In such domains, the key feature of interest is the location and orientation of maximal shearing planes. This paper describes a method that highlights this feature in stress tensor fields. It uses a plane-in-a-box glyph which provides a global perspective of shearing planes based on local analysis of tensors. The analysis can be performed over the entire domain, or the user can interactively specify where to introduce these glyphs. Alternatively, they can also be placed depending on the threshold level of several physical relevant parameters such as double couple and compensated linear vector dipole. Both methods are tested on stress tensor fields from geomechanics.

The study of physical models for knots has recently received much interest in the mathematics community. In this paper, we consider the ropelength model, which considers knots tied in an idealized rope. This model is interesting in pure mathematics, and has been applied to the study of a variety of problems in the natural sciences as well. Modeling and visualizing the tightening of knots in this idealized rope poses some interesting challenges in computer graphics. In particular, self-contact in a deformable rope model is a difficult problem which cannot be handled by standard techniques. In this paper, we describe a solution based on reformulating the contact problem and using constrained-gradient techniques from nonlinear optimization. The resulting animations reveal new properties of the tightening flow and provide new insights into the geometric structure of tight knots and links.

In this work we present a hardware-accelerated direct volume rendering system for visualizing multivariate wave functions in semiconducting quantum dot (QD) simulations. The simulation data contains the probability density values of multiple electron orbitals for up to tens of millions of atoms, computed by the NEMO3-D quantum device simulator software run on large-scale cluster architectures. These atoms form two interpenetrating crystalline face centered cubic lattices (FCC), where each FCC cell comprises the eight corners of a cubic cell and six additional face centers. We have developed compact representation techniques for the FCC lattice within PC graphics hardware texture memory, hardware-accelerated linear and cubic reconstruction schemes, and new multi-field rendering techniques utilizing logarithmic scale transfer functions. Our system also enables the user to drill down through the simulation data and execute statistical queries using general-purpose computing on the GPU (GPGPU).

The evacuation of buildings in the event of a fire requires careful planning of ventilation and evacuation routes during early architectural design stages. Different designs are evaluated by simulating smoke propagation using computational fluid dynamics (CFD). Visibility plays a decisive role in finding the nearest fire exit. This paper presents real-time volume rendering of transient smoke propagation conforming to standardized visibility distances. We visualize time dependent smoke particle concentration on unstructured tetrahedral meshes using a direct volume rendering approach. Due to the linear transfer function of the optical model commonly used in fire protection engineering, accurate pre-integration of diffuse color across tetrahedra can be carried out with a single 2D texture lookup. We reduce rounding errors during frame buffer blending by applying randomized dithering if high accuracy frame buffers are unavailable on the target platform. A simple absorption-based lighting model is evaluated in a preprocessing step using the same rendering approach. Back-illuminated exit signs are commonly used to indicate the escape route. As light emitting objects are visible further than reflective objects, the transfer function in front of illuminated exit signs must be adjusted with a deferred rendering pass.

In this paper, we present a volume roaming system dedicated to oil and gas exploration. Our system combines probe-based volume rendering with data processing and computing. The daily oil production and the estimation of the world proven-reserves directly affect the barrel price and have a strong impact on the economy. Among others, production and correct estimation are linked to the accuracy of the sub-surface model used for predicting oil reservoirs shape and size. Geoscientists build this model from the interpretation of seismic data, i.e. 3D images of the subsurface obtained from geophysical surveys. Our system couples visualization and data processing for the interpretation of seismic data. It is based on volume roaming along with efficient volume paging to manipulate the multi-gigabyte data sets commonly acquired during seismic surveys. Our volume rendering lenses implement high quality pre-integrated volume rendering with accurate lighting. They use a generic multi-modal volume rendering system that blends several volumes in the spirit of the "stencil" paradigm used in 2D painting programs. In addition, our system can interactively display non-polygonal isosurfaces painted with an attribute. Beside the visualization algorithms, automatic extraction of local features of the subsurface model also take full advantage of the volume paging.

Illustrations play a major role in the education process. Whether used to teach a surgical or radiologic procedure, to illustrate normal or aberrant anatomy, or to explain the functioning of a technical device, illustration significantly impacts learning. Although many specimens are readily available as volumetric data sets, particularly in medicine, illustrations are commonly produced manually as static images in a time-consuming process. Our goal is to create a fully dynamic three-dimensional illustration environment which directly operates on volume data. Single images have the aesthetic appeal of traditional illustrations, but can be interactively altered and explored. In this paper we present methods to realize such a system which combines artistic visual styles and expressive visualization techniques. We introduce a novel concept for direct multi-object volume visualization which allows control of the appearance of inter-penetrating objects via two-dimensional transfer functions. Furthermore, a unifying approach to efficiently integrate many non-photorealistic rendering models is presented. We discuss several illustrative concepts which can be realized by combining cutaways, ghosting, and selective deformation. Finally, we also propose a simple interface to specify objects of interest through three-dimensional volumetric painting. All presented methods are integrated into VolumeShop, an interactive hardware-accelerated application for direct volume illustration.

In this paper, we describe a taxonomy of generic graph related tasks and an evaluation aiming at assessing the readability of two representations of graphs: matrix-based representations and node-link diagrams. This evaluation bears on seven generic tasks and leads to important recommendations with regard to the representation of graphs according to their size and density. For instance, we show that when graphs are bigger than twenty vertices, the matrix-based visualization performs better than node-link diagrams on most tasks. Only path finding is consistently in favor of node-link diagrams throughout the evaluation

A major challenge of current visualization and visual data mining (VDM) frameworks is to support users in the orientation in complex visual mining scenarios. An important aspect to increase user support and user orientation is to use a history mechanism that, first of all, provides un- and redoing functionality. In this paper, we present a new approach to include such history functionality into a VDM framework. Therefore, we introduce the theoretical background, outline design and implementation aspects of a history management unit, and conclude with a discussion showing the usefulness of our history management in a VDM framework

The design and evaluation of most current information visualization systems descend from an emphasis on a user's ability to "unpack" the representations of data of interest and operate on them independently. Too often, successful decision-making and analysis are more a matter of serendipity and user experience than of intentional design and specific support for such tasks; although humans have considerable abilities in analyzing relationships from data, the utility of visualizations remains relatively variable across users, data sets, and domains. In this paper, we discuss the notion of analytic gaps, which represent obstacles faced by visualizations in facilitating higher-level analytic tasks, such as decision-making and learning. We discuss support for bridging the analytic gap, propose a framework for design and evaluation of information visualization systems, and demonstrate its use

Exploratory analysis of multidimensional data sets is challenging because of the difficulty in comprehending more than three dimensions. Two fundamental statistical principles for the exploratory analysis are (1) to examine each dimension first and then find relationships among dimensions, and (2) to try graphical displays first and then find numerical summaries (D.S. Moore, (1999). We implement these principles in a novel conceptual framework called the rank-by-feature framework. In the framework, users can choose a ranking criterion interesting to them and sort 1D or 2D axis-parallel projections according to the criterion. We introduce the rank-by-feature prism that is a color-coded lower-triangular matrix that guides users to desired features. Statistical graphs (histogram, boxplot, and scatterplot) and information visualization techniques (overview, coordination, and dynamic query) are combined to help users effectively traverse 1D and 2D axis-parallel projections, and finally to help them interactively find interesting features

High-throughput experiments such as gene expression microarrays in the life sciences result in large datasets. In response, a wide variety of visualization tools have been created to facilitate data analysis. Biologists often face a dilemma in choosing the best tool for their situation. The tool that works best for one biologist may not work well for another due to differences in the type of insight they seek from their data. A primary purpose of a visualization tool is to provide domain-relevant insight into the data. Ideally, any user wants maximum information in the least possible time. In this paper we identify several distinct characteristics of insight that enable us to recognize and quantify it. Based on this, we empirically evaluate five popular microarray visualization tools. Our conclusions can guide biologists in selecting the best tool for their data, and computer scientists in developing and evaluating visualizations

A digital lens is a user interface mechanism that is a potential solution to information mangement problems. We investigated the use of digital lensing applied to imagery analysis. Participants completed three different types of tasks (locate, follow, and compare) using a magnification lens with three different degrees of offset (aligned, adjacent, and docked) over a high-resolution aerial photo. Although no lens offset mode was significantly better than another, most participants preferred the adjacent mode for the locate and compare tasks, and the docked mode for the follow tasks. This paper describes the results of a user study of magnification lenses and provides new insights into preferences of and interactions with digital lensing.

ARNA is an interactive visualization system that supports comparison and alignment of RNA secondary structure. We present a new approach to RNA alignment that exploits the complex structure of the Smith-Waterman local distance matrix, allowing people to explore the space of possible partial alignments to discover a good global solution. The modular software architecture separates the user interface from computation, allowing the possibility of incorporating different alignment algorithms into the same framework.

We present Artifacts of the Presence Era, a digital installation that uses a geological metaphor to visualize the events in a physical space over time. The piece captures video and audio from a museum and constructs an impressionistic visualization of the evolving history in the space. Instead of creating a visualization tool for data analysis, we chose to produce a piece that functions as a souvenir of a particular time and place. We describe the design choices we made in creating this installation, the visualization techniques we developed, and the reactions we observed from users and the media. We suggest that the same approach can be applied to a more general set of visualization contexts, ranging from email archives to newsgroups conversations

Many fields of study produce time series datasets, and both the size and number of theses datasets are increasing rapidly due to the improvement of data accumulation methods such as small, cheap sensors and routine logging of events. Humans often fail to comprehend the structure of a long time series dataset because of the overwhelming amount of data and the range of different time scales at which there may be meaningful patterns. BinX is an interactive tool that provides dynamic visualization and manipulation of long time series datasets. The dataset is visualized through user controlled aggregation, augmented by various information visualization techniques.

Improvise is a fully-implemented system in which users build and browse multiview visualizations interactively using a simple shared-object coordination mechanism coupled with a flexible, expression-based visual abstraction language. By coupling visual abstraction with coordination, users gain precise control over how navigation and selection in the visualization affects the appearance of data in individual views. As a result, it is practical to build visualizations with more views and richer coordination in Improvise than in other visualization systems. Building and browsing activities are integrated in a single, live user interface that lets users alter visualizations quickly and incrementally during data exploration

In this case study we attempt to visualize a real-world dataset consisting of 600 recently published information visualization papers and their references. This is done by first creating a global layout of the entire graph that preserves any cluster structure present. We then use this layout as a basis to define a hierarchical clustering. The clusters in this hierarchy are labelled using keywords supplied with the dataset, allowing insight into the clusters semantics.