Scientific Visualization Systems Research Articles

ElVis: A System for the Accurate and Interactive Visualization of High-Order Finite Element Solutions.

This paper presents the Element Visualizer (ElVis), a new, open-source scientific visualization system for use with high-order finite element solutions to PDEs in three dimensions. This system is designed to minimize visualization errors of these types of fields by querying the underlying finite element basis functions (e.g., high-order polynomials) directly, leading to pixel-exact representations of solutions and geometry. The system interacts with simulation data through runtime plugins, which only require users to implement a handful of operations fundamental to finite element solvers. The data in turn can be visualized through the use of cut surfaces, contours, isosurfaces, and volume rendering. These visualization algorithms are implemented using NVIDIA's OptiX GPU-based ray-tracing engine, which provides accelerated ray traversal of the high-order geometry, and CUDA, which allows for effective parallel evaluation of the visualization algorithms. The direct interface between ElVis and the underlying data differentiates it from existing visualization tools. Current tools assume the underlying data is composed of linear primitives; high-order data must be interpolated with linear functions as a result. In this work, examples drawn from aerodynamic simulations-high-order discontinuous Galerkin finite element solutions of aerodynamic flows in particular-will demonstrate the superiority of ElVis' pixel-exact approach when compared with traditional linear-interpolation methods. Such methods can introduce a number of inaccuracies in the resulting visualization, making it unclear if visual artifacts are genuine to the solution data or if these artifacts are the result of interpolation errors. Linear methods additionally cannot properly visualize curved geometries (elements or boundaries) which can greatly inhibit developers' debugging efforts. As we will show, pixel-exact visualization exhibits none of these issues, removing the visualization scheme as a source of uncertainty for engineers using ElVis.

Design and Algorithms of a Rainfall Analysis System

We fully discuss algorithms of Kriging interpolation, isoline drawing and contour map filling which are important in scientific data visualization and geographical information systems. Though these topics are classical in the theory of geographical systems and have undergone intense studies for many years, these algorithms are not easily found elsewhere in a so detailed and complete form, notably the contour map filling is devised totally through our own much effort. To be more practical, we also present the popular DLL-and-XML-technology based architecture of a real rainfall analysis system which has been used effectively in many cities of ZheJiang province. This greatly eased the hard task of rainfall isoline drawing, formerly furnished mainly by hand. The sources of input rain data are vast, ranging from realtime recording at rain stations to the more advanced radar measurement, as long as these data were stored in databases or files. Both the algorithms and the framework of our software can be used without change to other circumstance such as mountains' height contour and mineral distributions. The algorithms introduced here are robust and the overall functions of this software can rival those of the famous general purpose GIS software-Surfer by Goldensoft Corp. both in speed and appearance.

Augmented Reality Prototype for Visualising Large Sensors’ Datasets

This paper addressed the development of an augmented reality (AR) based scientific visualization system prototype that supports identification, localisation, and 3D visualisation of oil leakages sensors datasets. Sensors generates significant amount of multivariate datasets during normal and leak situations which made data exploration and visualisation daunting tasks. Therefore a model to manage such data and enhance computational support needed for effective explorations are developed in this paper. A challenge of this approach is to reduce the data inefficiency. This paper presented a model for computing information gain for each data attributes and determine a lead attribute.The computed lead attribute is then used for the development of an AR-based scientific visualization interface which automatically identifies, localises and visualizes all necessary data relevant to a particularly selected region of interest (ROI) on the network. Necessary architectural system supports and the interface requirements for such visualizations are also presented.

Using VisTrails and Provenance for Teaching Scientific Visualization

Abstract Over the last 20 years, visualization courses have been developed and offered at universities around the world. Many of these courses use established visualization libraries and tools (e.g. VTK, ParaView, AVS, VisIt) as a way to provide students a hands‐on experience, allowing them to prototype and explore different visualization techniques. In this paper, we describe our experiences using VisTrails as a platform to teach scientific visualization. VisTrails is an open‐source system that was designed to support exploratory computational tasks such as visualization and data analysis. Unlike previous scientific workflow and visualization systems, VisTrails provides a comprehensive provenance management infrastructure. We discuss how different features of the system, and in particular, the provenance information have changed the dynamics of the Scientific Visualization course we offer at the University of Utah. We also describe our initial attempts at using the provenance information to better assess our teaching techniques and student performance.

Best papers from the 12th Pacific-Asia conference on knowledge discovery and data mining (PAKDD2008)

The Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) has been held every year since 1997. PAKDD 2008, the 12th in the series, was held in Osaka, Japan on May 20–23, 2008. PAKDD is a leading international conference in the area of data mining. It provides an international forum for researchers and industry practitioners to share their new ideas, original research results and practical development experiences from all KDD-related areas including data mining, data warehousing, machine learning, databases, statistics, knowledge acquisition, automatic scientific discovery, data visualization, causal induction and knowledge-based systems. We received a total of 312 research papers from34 countries and regions inAsia, Australia, North America, South America, Europe and Africa. Only approximately 11.9% of the these submissions were accepted as long papers, 12.8% of them were accepted as regular papers, and 11.5% of them were accepted as short papers upon rigorous reviews by two or three reviewers, discussions by the reviewers under the supervision of an area chair and judgment by the Program Committee Co-chairs. The highest rated papers in the review process were further evaluated by the Program Committee Co-chairs, and two papers were selected for the Best Paper Award and the Best Paper Runner-up Award. In addition to these award-winning papers, two outstanding papers were also nominated for this special issue. The authors of the four selected papers were asked to substantially extend the contents of their papers after the

A110 原子力分野におけるグリッド環境での可視化システム

An innovative scientific visualization system is needed to integratedly visualize large amount of data which are distributedly generated in remote locations as a result of a large-scale numerical simulation using a grid environment. One of the important functions in such a visualization system is a parallel visualization which enables to visualize data using multiple CPUs of a supercomputer. The other is a distributed visualization which enables to execute visualization processes using a local client computer and remote computers. We have developed a toolkit including these functions in cooperation with the commercial visualization software AVS/Express, called Parallel Support Toolkit (PST). PST can execute visualization processes with three kinds of parallelism (data parallelism, task parallelism and pipeline parallelism) using local and remote computers. We have evaluated PST for large amount of data generated by a nuclear fusion simulation. Here, two supercomputers Altix3700Bx2 and Prism installed in JAEA are used. From the evaluation, it can be seen that PST has a potential to efficiently visualize large amount of data in a grid environment.

Scivis

Visualization affects the process of analysis and design in a number of ways. Applying visualization concepts to scientific data gives scientists greater abilities to understand their data. We have designed and implemented Scivis, which is a collaborative scientific visualization system. Scivis is implemented in Java, taking full advantage of its benefits. We have concentrated on three important issues: ease of use, a collaborative framework, and a highly customizable system. Since its introduction, Scivis has generated significant interest throughout many research labs. © 1998 John Wiley & Sons, Ltd.

Extraction of vector information using a novel tactile display

A tactile stimulation device capable of displaying sophisticated animated patterns to a human hand has been designed and constructed. In a scientific visualization scenario, vectors of varying magnitude and direction are encoded, thus leaving the visual display free to show other information. The tactile information can be synchronized with that displayed visually and aurally, creating a multi-dimensional, multi-modal scientific visualization system. The design and operation of the tactile display device are described. An experiment that explores the vector magnitude and direction acuity of observers using this display is also presented. The principal findings are that both variations in magnitude and direction could be accurately discerned, though magnitude response showed a small degree of non-linearity. Furthermore, these two dimensions showed a high degree of orthogonality. The observers found the device clear and natural to use, and the manner in which the information was encoded upon it was reported to be easily and intuitively interpretable.

INTEGRATING A GEOGRAPHIC INFORMATION SYSTEM, A SCIENTIFIC VISUALIZATION SYSTEM, AND A PRECIPITATION MODEL1

ABSTRACT: Investigating natural, potential, and human‐induced impacts on hydrologic systems commonly requires complex modeling with overlapping data requirements, plus massive amounts of one‐ to four‐dimensional data at multiple scales and formats. Given the complexity of most hydrologic studies, the requisite software infrastructure must incorporate many components including simulation modeling and spatial analysis with a flexible, intuitive display. Integrating geographic information systems (GIS) and scientific visualization systems (SVS) provides such an infrastructure. This paper describes an integrated system consisting of an orographic precipitation model, a GIS, and an SVS. The results of this study provide a basis for improving the understanding of hydro‐climatic processes in mountainous regions. An additional benefit of the integrated system, the value of which is often underestimated, is the improved ability to communicate model results, leading to a broader understanding of the model assumptions, sensitivities, and conclusions at a management level.

Visual Computing Laboratory

It would be difficult to overestimate the importance of visual information in current computer systems. Visual computing, which embraces processing, interpreting, modeling, assimilating, storing, retrieving, and synthesizing visual information, now plays a crucial role in many fields. These include multimedia, virtual reality, robotics, scientific visualization, and communications systems. And the demand for further integration of visual information into these areas shows every sign of continuing unabated. Under the direction of Ramesh Jain, the Visual Computing Laboratory at the University of California, San Diego, was established as a center for innovative visual computing research to address the requirements of these applications in next-generation computer technologies. As such, the Visual Computing Lab hosts a group of researchers working in a variety of areas, notably multimedia databases, information assimilation, interactive video, and visual interaction through gesture recognition. This article presents a high-level overview of activities in the Visual Computing Laboratory and provides some details on prototype systems that we are currently developing. >

Virtual reality in scientific visualization

The use of virtual environments in scientific visualization is discussed. Successful examples are surveyed in depth. Lessons about the usefulness and applicability of virtual environments to scientific visualization are drawn. Lessons learned from these applications for the development of virtual environments are also drawn. Difficulties in the application of virtual environments to scientific visualization are discussed. Problems encountered in virtual reality implementations of scientific visualization systems are briefly surveyed. Possible futures are briefly examined.

Delivering data interpretation: From GFLOPS to insight

The quest to deliver computers with teraflop computing power introduces several ancillary technical challenges. One of the most obvious challenges involves the capability to interpret the enormous quantity of data resulting from investigations using today's supercomputers. Data interpretation requires several techniques: printouts, graphics, scientific visualization, and multi-sensory systems. The need to more efficiently interpret large datasets led the US Army Engineers Waterways Experiment Station to establish a scientific visualization center. This center, established in the fall of 1990, provides assistance with the adaptation and implementation of emerging data interpretation techniques to the 800+ researchers at the national laboratory. This paper summarizes the collective experiences of The Center. Experience with commercial visualization software, public domain software, internally developed software, visualization techniques, virtual reality systems, and hardware facilities is presented.

The Visualization Input Pipeline - Enabling Semantic Interaction in Scientific Visualization

Scientific Visualization systems are primarily output-oriented, Users can specify and change parameters that are controlling the visualization process, which will result in different data representations or images respectively. But no mechanism is provided to really interact with the application data (semantic interaction) that has been changed step by step by the process of visualization. In this paper general concepts are elaborated and presented to achieve semantic interaction in dataflow environments for Scientific Visualization.

Scientific visualization: practices and promises

Scientific visualization is one of the most influential forces in the way computers are used in research. The components, users and benefits of scientific visualization systems are described.

Trends and concerns in digital cartography

Digital cartography is the technology concerned with the construction and use of computer-based systems for the practice of cartography and its applications. The paper starts with a brief introduction to cartography and cartographic maps. It then provides an overview of some of the major trends and concerns in digital cartography. The subfields of visual and digital mapping are now well established and attention is being focused on more onerous activities, such as formal theorising about cartographic processes through automated production of maps; reliable and efficient management of integrated but changeable spatial databases; and, appropriate packaging of technology for geographical information systems. The paper also includes some comments on the contribution of CAD to cartography and on the not very well understood relationships between interactive cartography and the fast-growing, related disciplines of scientific visualization and geographical information systems.