Brian E. Paul

Interactive visualization of Earth and space science computations

Scientists often view computer algorithms as risk-filled black boxes. The barrier between scientists and their computations can be bridged by techniques that make the internal workings of algorithms visible and that allow scientists to experiment with their computations. We describe two interactive systems developed at the University of Wisconsin-Madison Space Science and Engineering Center (SSEC) that provide these capabilities to Earth and space scientists. These visualization packages help scientists see the internal workings of their algorithms and thus understand their computations.<<ETX>>

Display of scientific data structures for algorithm visualization

A technique for defining graphical depictions for all the data types defined in an algorithm is presented. The ability to display arbitrary combinations of an algorithms data objects in a common frame of reference, coupled with interactive control of algorithm execution, provides a powerful way to understand algorithm behavior. Type definitions are constrained so that all primitive values occurring in data objects are assigned scalar types. A graphical display, including user interaction with the display, is modeled by a special data type. Mappings from the scalar types into the display model type provide a simple user interface for controlling how all data types are depicted, without the need for type-specific graphics logic.<<ETX>>

A lattice model for data display

In order to develop a foundation for visualization, we develop lattice models for data objects and displays that focus on the fact that data objects are approximations to mathematical objects and real displays are approximations to ideal displays. These lattice models give us a way to quantize the information content of data and displays and to define conditions on the visualization mappings from data to displays. Mappings satisfy these conditions if and only if they are lattice isomorphisms. We show how to apply this result to scientific data and display models, and discuss how it might be applied to recursively defined data types appropriate for complex information processing.<<ETX>>

Virtual Chesapeake Bay: interacting with a coupled physical/biological model

The Chesapeake Bay Virtual Environment (CBVE) is a multidisciplinary, collaborative project that fuses 3D visualizations of numerically generated output, observations and other data products into a large-scale, interactive virtual world that supports investigation of coupled physical/biological and environmental processes. Although still under development, CBVE provides an application framework for integrating circulation and biological models with the computer visualization paradigm of the virtual world. In this article, we first briefly describe the physical environment and the observed effects of winds, tides and river runoff on the Chesapeake Bay system. Then we describe the CBVE components and conclude with our efforts directed at understanding how environmental variability may affect the recruitment and retention of the larval phase of certain local marine species.

Exploring Coupled Atmosphere-Ocean Models Using Vis5D

A distributed client/server system can be used to visualize very large simulation data sets. An example of a very large simulation data set is a 100-year simulation of the Earths coupled atmosphere-ocean system. This model run was produced by an Argonne National Laboratory/University of Wisconsin collaborative project that is studying atmosphere-ocean coupling dynamics to understand the intrinsic low-frequency variability of the climate system. This understanding is crucial for the prediction and detec tion of human impacts on the Earths climate. To visually explore this simulation, an IBM SP-2 is used as a data server and a pair of SGI Onyxes driving a CAVE are used as a graphics client. The SP-2 server divides the data set into sections that will fit in the memory of the graphics client. The data set is divided along the time axis. One data set section covers the entire 100-year span of the simula tion at reduced-time resolution, while the other data set sections cover short subintervals at full-time resolution. The visualization user interface allows users to switch between low and high time resolution.

The VIS-AD Data Model: Integrating Metadata and Polymorphic Display with a Scientific Programming Language

The VIS-AD data model integrates metadata about the precision of values, including missing data indicators and the way that arrays sample continuous functions, with the data objects of a scientific programming language. The data objects of this data model form a lattice, ordered by the precision with which they approximate mathematical objects. We define a similar lattice of displays and study visualization processes as functions from data lattices to display lattices. Such functions can be applied to visualize data objects of all data types and are thus polymorphic.

Interactivity and the Dimensionality of Data Displays

Using mathematical models of data and displays, we illustrate the importance of distinguishing between independent and dependent variables when counting the dimensions of data sets and displays. The number of independent variables occurring as dimensions of a display model is the most important factor determining its information carrying capacity. Independent variables in a display model also require interactive techniques for their implementation, as illustrated by our VIS-AD system and Beshers’ and Feiner’s worlds within worlds technique. Thus interactivity is critical for visually communicating large amounts of information, and the perceptual properties of interaction techniques are an important topic for visualization research.

Visualization requirements in the atmospheric and environmental sciences (five case study reports)

Reports from five research centers involved with atmospheric and environmental visualization issues are presented in this case study. Visualization with heterogeneous computer architectures is highlighted in the US EPA Scientific Visualization Center discussion. The NASA Marshall Space Flight Center effort to develop the multidimensional analysis of sensor systems (MASS) environment is presented. Florida State Universitys building of a new scientific visualization package, Sci An, is reported. This is followed by a discussion of the design and implementation of VIS-AD, an experimental laboratory for developing scientific algorithms, at the University of Wisconsin-Madison. The visualization of global atmospheric data at IBM Thomas J. Watson Research Center is highlighted.<<ETX>>