William L. Hibbard

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>>

Visualizing large data sets in the earth sciences

The authors describe the capabilities of McIDAS , an interactive visualization system that is vastly increasing the ability of earth scientists to manage and analyze data from remote sensing instruments and numerical simulation models. McIDAS provides animated three-dimensional images and highly interactive displays. The software can manage, analyze, and visualize large data sets that span many physical variables (such as temperature, pressure, humidity, and wind speed), as well as time and three spatial dimensions. The McIDAS system manages data from at least 100 different sources. The data management tools consist of data structures for storing different data types in files, libraries of routines for accessing these data structures, system commands for performing housekeeping functions on the data files, and reformatting programs for converting external data to the systems data structures. The McIDAS tools for three-dimensional visualization of meteorological data run on an IBM mainframe and can load up to 128-frame animation sequences into the workstations. A highly interactive version of the system can provide an interactive window into data sets containing tens of millions of points produced by numerical models and remote sensing instruments. The visualizations are being used for teaching as well as by scientists.<<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.

Java distributed components for numerical visualization in VisAD

Combining a flexible data model and distributed objects, they support the sharing of data, visualizations, and user interfaces among multiple data sources, computers, and scientific disciplines.

Computer-generated imagery for 4-D meteorological data

The University of Wisconsin-Madison Space Science and Engineering Center is developing animated stereo display terminals for use with McIDAS (Man-computer Interactive Data Access System). This paper describes image-generation techniques which have been developed to take maximum advantage of these terminals, integrating large quantities of four-dimensional meteorological data from balloon and satellite soundings, satellite images, doppler and volumetric radar, and conventional surface observations. The images have been designed to use perspective, shading, hidden-surface removal, and transparency to augment the animation and stereo-display geometry. They create an illusion of a moving three-dimensional model of the atmosphere so vivid that you feel like you can reach into the display and touch it. This paper describes the design of these images and a number of rules of thumb for generating four-dimensional meteorological displays.

4-D display of meteorological data

The Man-computer Interactive Data Access System (McIDAS) developed at the University of Wisconsin-Madison Space Science and Engineering Center (UW-SSEC) collects large quantities of meteorological data in real time for storage, analysis and display on multi-frame video terminals. Software is being developed on the McIDAS system which produces 3-D images from a variety of meteorological data for stereo display in short animation sequences. These animation sequences are produced in a few minutes. The user controls the space and time extents, contents and information density of the display.

Database Issues for Data Visualization: Developing a Data Model

The remainder of this paper discusses the major issues related to the development of data models for scientific visualization which were identified by the data model subgroup at the IEEE Workshop on Database Issues in Visualization held in October 1993 in San Jose, California. The issues include the need to develop a reasonable taxonomy to apply to data models, the definition of metadata (or ancillary data), the notion of levels of abstraction available for defining a data model, the nature and role of queries in a data model, and the effects of data errors on a data model.