Volume rendering is a technique for visualizing 3D arrays of sampled data. It has applications in areas such as medical imaging and scientific visualization, but its use has been limited by its high computational expense. Early implementations of volume rendering used brute-force techniques that require on the order of 100 seconds to render typical data sets on a workstation. Algorithms with optimizations that exploit coherence in the data have reduced rendering times to the range of ten seconds but are still not fast enough for interactive visualization applications. In this thesis we present a family of volume rendering algorithms that reduces rendering times to one second. First we present a scanline-order volume rendering algorithm that exploits coherence in both the volume data and the image. We show that scanline-order algorithms are fundamentally more efficient than commonly-used ray casting algorithms because the latter must perform analytic geometry calculations (e.g. intersecting rays with axis-aligned boxes). The new scanline-order algorithm simply streams through the volume and the image in storage order. We describe variants of the algorithm for both parallel and perspective projections and

Paradyn is a performance measurement tool for parallel and distributed programs. Paradyn uses several novel technologies so that it scales to long running programs (hours or days) and large (thousand node) systems, and automates much of the search for performance bottlenecks. It can provide precise performance data down to the procedure and statement level. Paradyn is based on a dynamic notion of performance instrumentation and measurement. Unmodified executable files are placed into execution and then performance instrumentation is inserted into the application program and modified during execution. The instrumentation is controlled by the Performance Consultant module, that automatically directs the placement of instrumentation. The Performance Consultant has a well-defined notion of performance bottlenecks and program structure, so that it can associate bottlenecks with specific causes and specific parts of a program. Paradyn controls its instrumentation overhead by monitoring the cost of its data collection, limiting its instrumentation to a (user controllable) threshold. The instrumentation in Paradyn can easily be configured to accept new operating system, hardware, and application specific performance data. It also provides an open interface for performance visualization, and a simple programming library to allow these visualizations to interface to Paradyn. Paradyn can gather and present performance data in terms of high-level parallel languages (such as data parallel Fortran) and can measure programs on massively parallel computers, workstation clusters, and heterogeneous combinations of these systems. 1.

The lineage of a datum records its processing history. Because such information can be used to trace the source of anomalies and errors in processed data sets, it is valuable to users for a variety of applications including investigation of anomalies and debugging. Traditional data lineage approaches rely on metadata. However, metadata does not scale well to fine-grained lineage, especially in large data sets. For example, it is not feasible to store all of the information necessary to trace from a specific floating point value in a processed data set to a particular satellite image pixel in a source data set. In this paper, we propose a novel method to support finegrained data lineage. Rather than relying on metadata, our approach lazily computes lineage using a limited amount of information about the processing operators and the base data. We introduce the notions of weak inversion and verification. While our system does not perfectly invert the data, it uses weak inversion and verification to provide a number of guarantees about the lineage it generates. We propose a design for the implementation of weak inversion and verification in an object-relational database management system. 1.

) M. Livny, R. Ramakrishnan, K. Beyer, G. Chen, D. Donjerkovic, S. Lawande, J. Myllymaki and K. Wenger Department of Computer Sciences, University of Wisconsin--Madison 1210 W. Dayton St., Madison, Wisconsin 53706 Tel: (608)262-6611, Fax: (608)262-9777 fmiron,raghu,beyer,guangshu,donjerko,ssl,jussi,wengerg@cs.wisc.edu Abstract DEVise is a data exploration system that allows users to easily develop, browse, and share visual presentations of large tabular datasets (possibly containing or referencing multimedia objects) from several sources. The DEVise framework, implemented in a tool that has been already successfully applied to a variety of real applications by a number of user groups, makes several contributions. In particular, it combines support for extended relational queries with powerful data visualization features. Datasets much larger than available main memory can be handled---DEVise is currently being used to visualize datasets well in excess of 100MB--- and data can be in...

We describe a system, called GPL, that implements a language for quantitative graphics. The structure of this system differs from existing statistical graphics, visualization, and mapping systems. Instead of treating a graphics display as a viewer for underlying data, GPL treats data as an accessory to viewing a graph. GPL is based on the mathematical definition of the graph of a function and uses that definition to organize data linked to the graph. To be published in Journal of Computational and Graphical Statistics. GPL has been renamed nViZn

... stochastic Brownian motion. The rate of this diffusion can give clues to the structure of underlying tissues. In some tissues the rate is anisotropic -- faster in some directions than others. Diffusionrate images are second-order tensor fields and can be calculated from diffusion-weighted magnetic resonance images. A 2D diffusion tensor image (DTI) and an associated anatomical scalar field, created during the tensor calculation, define seven values at each spatial location. Visually representing these images is a challenge because they contain so many inter-related components. We present two new methods for visually representing DTIs. The first method displays an array of ellipsoids where the shape of each ellipsoid represents one tensor value. The novel aspect of this representation is that the ellipsoids are all normalized to approximately the same size so that they can be displayed simultaneously in context. The second method uses concepts from oil painting to represent the seven-valued data with multiple layers of varying brush strokes. Both methods successfully display most or all of the information in DTIs and provide exploratory methods for understanding them. The ellipsoid method has a simpler interpretation and explanation than the painting-motivated method; the painting-motivated method displays more of the information and is easier to read quantitatively. We demonstrate the methods on images of the mouse spinal cord. The visualizations show significant differences between spinal cords from mice suffering from Experimental Allergic Encephalomyelitis (EAE) and spinal cords from wild-type mice. The differences are consistent with differences shown histologically and suggest that our new non-invasive imaging methodology and visualization of the results could have...

In biological tissue, water is ubiquitous and constantly in motion. This motion of water inside biological tissue is called diffusion. Water usually diffuses at different rates both in different locations and along different directions at one location. The difference of diffusion rates at one location is called anisotropy. The following pictures show three types of diffusion illustrated by the ellipsoids. The ellipsoid would be

Information has become interactive. Information visualization is the design and creation of interactive graphic depictions of information by combining principles in the disciplines of graphic design, cognitive science, and interactive computer graphics. As the volume and complexity of the data increases, users require more powerful visualization tools that allow them to more effectively explore large abstract datasets. This

In information visualization, as the volume and complexity of the data increases, researchers require more powerful visualization tools that enable them to more effectively explore multidimensional datasets. In this paper, we discuss the general utility of a novel visualization spreadsheet framework. Just as a numerical spreadsheetenables exploration of numbers, a visualization spreadsheet enables exploration of visual forms of information. We show that the spreadsheet approach facilitates certain information visualization tasks that are more difficult using other approaches. Unlike traditional spreadsheets, which store only simple data elements and formulas in each cell, a visualization spreadsheetcell can hold anentire complex data set, selection criteria, viewing specifications, and other information needed for a full-fledged information visualization. Similarly, inter-cell operations are far more complex, stretching beyond simple arithmetic and string operations to encompass a range of domain-specific operators. We have built two prototype systems that illustrate some of these research issues. The underlying approach in our work allows domain experts to define new data types and data operations, and enables visualization experts to incorporate new visualizations, viewing parameters, and view operations. 1

This paper describes three experiments that investigate the ability of humans to perform high-speed visual estimation. This work is part of an ongoing study of techniques which allow rapid and accurate visualization of large multidimensional datasets. Scientific visualization in computer graphics is a relatively new field of research. The term "visualization" was used by a 1987 panel sponsored by the National Science Foundation (NSF) discussing how to apply computer science to data analysis problems (McCormick et al., 1987). The panel defined the "domain of visualization" to include the development of general purpose tools and the study of research problems that arise in the process. A variety of methods have been used to convert raw data into a more usable visual format. Both Tufte