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Visualization: Future Technology and Practices for Computational Science and Engineering

Copyright © 2012. 33 pages.
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DOI: 10.4018/978-1-61350-116-0.ch016
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Leng, Joanna, Theresa-Marie Rhyne and Wes Sharrock. "Visualization: Future Technology and Practices for Computational Science and Engineering." Handbook of Research on Computational Science and Engineering: Theory and Practice. IGI Global, 2012. 381-413. Web. 16 Apr. 2014. doi:10.4018/978-1-61350-116-0.ch016


Leng, J., Rhyne, T., & Sharrock, W. (2012). Visualization: Future Technology and Practices for Computational Science and Engineering. In J. Leng, & W. Sharrock (Eds.) Handbook of Research on Computational Science and Engineering: Theory and Practice (pp. 381-413). Hershey, PA: Engineering Science Reference. doi:10.4018/978-1-61350-116-0.ch016


Leng, Joanna, Theresa-Marie Rhyne and Wes Sharrock. "Visualization: Future Technology and Practices for Computational Science and Engineering." In Handbook of Research on Computational Science and Engineering: Theory and Practice, ed. J. Leng and Wes Sharrock, 381-413 (2012), accessed April 16, 2014. doi:10.4018/978-1-61350-116-0.ch016

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Visualization: Future Technology and Practices for Computational Science and Engineering
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This chapter focuses on state of the art at the intersection of visualization and CSE. From understanding current trends it looks to future applications for these technologies. Some background is provided into visualization and its relation with CSE as well as with software and hardware frameworks that visualization systems depend on. Important emerging research areas are identified, including: interactive simulation and computational steering; collaborative, remote visualization and visualization services; VR technologies for visualization; user experience and assessment; teaching and serious gaming; communicating science to the public; ultra-scale visualization; and computational aesthetics. This should present the readers with real possibilities for CSE no matter what their disciplinary background.
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Visualization is a technology that provides pictorial descriptions of results from computations and simulations and as such it is a vital component of CSE. It is a fairly mature technology providing not only an ever widening set of presentational techniques but also, among other things, a framework for visualization systems that can be extended to remote/distributed visualization services, techniques for handling and rendering large data and the more efficient exploitation of high performance computing (HPC). Though visualization is very prominent in Computational Science and Engineering (CSE) it can be applied to many other areas such as data mining and informatics. Just as computational science is divided into separate communities interested in specific application areas or mathematical/programming approaches so too is visualization.

This chapter focuses on the general area of visualization. Just as there are many distinct mathematical approaches to developing computational simulations each with their own dedicated communities, visualization also divides itself amongst different application areas and/or mathematical approaches. Here, however, we will use application areas or programmatic issues only to illustrate more general trends, except when discussing special cases that are part of the current research scene. Interested readers should consult textbooks referenced for more balanced and wide ranging examples.

Who Should Read This Chapter

Researchers with a variety of backgrounds and job roles will have an interest in visualization. This chapter starts with the general to build the reader’s understanding of pertinent issues (the background of visualization; its relation to computer graphics and computer science departments; the visualization pipeline and how this abstraction relates to the general frame work of visualization systems as well as its dependence on hardware; ending with the background to CSE). The chapter then looks at seven visualization research areas relevant to CSE:

  • Interactive simulation and computational steering;

  • Collaborative, remote visualization and visualization services;

  • VR technologies for visualization;

  • User experience and assessment;

  • Teaching and serious gaming;

  • Communicating science to the public;

  • Ultra-scale visualization;

  • And computational aesthetics.

All readers should get some benefit from these, but we have mainly aimed at three kinds of readers:

  • Visualizers, who are often specialized in one area of visualization, may find the discussion of more general issues useful as well as finding interest in issues in other areas of visualization research.

  • Practitioners of CSE with interests in a specific area of visualization will have a variety of needs, skills and knowledge. They will benefit from the general issues and also from selecting relevant topics from those discussed in more detail.

  • CSE managers and policy makers: in general, this group needs to be aware of the hardware and software needs the visualization professionals require to do their jobs. The CSE manager needs to understand the separation and intertwined nature of CSE and visualization and the way their needs differ with the CSE problems under consideration.


Complete Chapter List

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Table of Contents
Joanna Leng, Wes Sharrock
Chapter 1
Gabriele Jost, Alice E. Koniges
The upcoming years bring new challenges in high-performance computing (HPC) technology. Fundamental changes in the building blocks of HPC hardware... Sample PDF
Hardware Trends and Implications for Programming Models
Chapter 2
Ivan Girotto, Robert M. Farber
This chapter focuses on the technical/commercial dynamics of multi-threaded hardware architecture development, including a cost/benefit account of... Sample PDF
Multi-Threaded Architectures: Evolution, Costs, Opportunities
Chapter 3
Domingo Benitez
Many accelerator-based computers have demonstrated that they can be faster and more energy-efficient than traditional high-performance multi-core... Sample PDF
High-Performance Customizable Computing
Chapter 4
Rasit O. Topaloglu, Swati R. Manjari, Saroj K. Nayak
Interconnects in semiconductor integrated circuits have shrunk to nanoscale sizes. This size reduction requires accurate analysis of the quantum... Sample PDF
High-Performance Computing for Theoretical Study of Nanoscale and Molecular Interconnects
Chapter 5
Prashobh Balasundaram
This chapter presents a study of leading open source performance analysis tools for high performance computing (HPC). The first section motivates... Sample PDF
Effective Open-Source Performance Analysis Tools
Chapter 6
David Worth, Chris Greenough, Shawn Chin
The purpose of this chapter is to introduce scientific software developers to software engineering tools and techniques that will save them much... Sample PDF
Pragmatic Software Engineering for Computational Science
Chapter 7
Diane Kelly, Daniel Hook, Rebecca Sanders
The aim of this chapter is to provide guidance on the challenges and approaches to testing computational applications. Testing in our case is... Sample PDF
A Framework for Testing Code in Computational Applications
Chapter 8
Judith Segal, Chris Morris
There are significant challenges in developing scientific software for a broad community. In this chapter, we discuss how these challenges are... Sample PDF
Developing Software for a Scientific Community: Some Challenges and Solutions
Chapter 9
Fumie Costen, Akos Balasko
The computational architecture of Enabling Grids for E-sciencE is introduced as it made our code porting very challenging, and the discussion... Sample PDF
Opportunities and Challenges in Porting a Parallel Code from a Tightly-Coupled System to the Distributed EU Grid, Enabling Grids for E-sciencE
Chapter 10
Abid Yahya, Farid Ghani, R. Badlishah Ahmad, Mostafijur Rahman, Aini Syuhada, Othman Sidek, M. F. M. Salleh
This chapter presents performance of a new technique for constructing Quasi-Cyclic Low-Density Parity-Check (QC-LDPC) encrypted codes based on a row... Sample PDF
Development of an Efficient and Secure Mobile Communication System with New Future Directions
Chapter 11
Hubertus J. J. van Dam
Quantum chemistry was a compute intensive field from the beginning. It was also an early adopter of parallel computing, and hence, has more than... Sample PDF
Parallel Quantum Chemistry at the Crossroads
Chapter 12
Marc Hafner, Heinz Koeppl
With the advances in measurement technology for molecular biology, predictive mathematical models of cellular processes come in reach. A large... Sample PDF
Stochastic Simulations in Systems Biology
Chapter 13
C. T. J. Dodson
Many real processes have stochastic features which seem to be representable in some intuitive sense as `close to Poisson’, `nearly random’, `nearly... Sample PDF
Some Illustrations of Information Geometry in Biology and Physics
Chapter 14
Stefania Tomasiello
Though relatively unknown, the Differential Quadrature Method (DQM) is a promising numerical technique that produces accurate solutions with less... Sample PDF
DQ Based Methods: Theory and Application to Engineering and Physical Sciences
Chapter 15
Marco Evangelos Biancolini
Radial Basis Functions (RBF) mesh morphing, its theoretical basis, its numerical implementation, and its use for the solution of industrial... Sample PDF
Mesh Morphing and Smoothing by Means of Radial Basis Functions (RBF): A Practical Example Using Fluent and RBF Morph
Chapter 16
Joanna Leng, Theresa-Marie Rhyne, Wes Sharrock
This chapter focuses on state of the art at the intersection of visualization and CSE. From understanding current trends it looks to future... Sample PDF
Visualization: Future Technology and Practices for Computational Science and Engineering
Chapter 17
Peter Sarlin
Since the 1980s, two severe global waves of sovereign defaults have occurred in less developed countries (LDCs): the LDC defaults in the 1980s and... Sample PDF
Visualizing Indicators of Debt Crises in a Lower Dimension: A Self-Organizing Maps Approach
Chapter 18
Iain Barrass, Joanna Leng
Since infectious diseases pose a significant risk to human health many countries aim to control their spread. Public health bodies faced with a... Sample PDF
Improving Computational Models and Practices: Scenario Testing and Forecasting the Spread of Infectious Disease
Chapter 19
Eldon R. Rene, Sung Joo Kim, Dae Hee Lee, Woo Bong Je, Mirian Estefanía López, Hung Suck Park
Sequencing batch reactor (SBR) is a versatile, eco-friendly, and cost-saving process for the biological treatment of nutrient-rich wastewater, at... Sample PDF
Artificial Neural Network Modelling of Sequencing Batch Reactor Performance
Chapter 20
Joanna Leng, Wes Sharrock
Computational Science and Engineering (CSE) is an emerging, rapidly developing, and potentially very significant force in changing scientific... Sample PDF
The State of Development of CSE
Chapter 21
Kerstin Kleese van Dam, Mark James, Andrew M. Walker
This chapter describes the key principles and components of a good data management system, provides real world examples of how these can be... Sample PDF
Integrating Data Management and Collaborative Sharing with Computational Science Research Processes
Chapter 22
Jens Jensen, David L. Groep
Modern science increasingly depends on international collaborations. Large instruments are expensive and have to be funded by several countries, and... Sample PDF
Security and Trust in a Global Research Infrastructure
Chapter 23
Matt Ratto
Computational science and engineering (CSE) technologies and methods are increasingly considered important tools for the humanities and are being... Sample PDF
CSE as Epistemic Technologies: Computer Modeling and Disciplinary Difference in the Humanities
Chapter 24
Phillip L. Manning, Peter L. Falkingham
Dinosaurs successfully conjure images of lost worlds and forgotten lives. Our understanding of these iconic, extinct animals now comes from many... Sample PDF
Science Communication with Dinosaurs

Key Terms in this Chapter

Serious Games: A game designed for any purpose rather than entertainment. Serious games are considered useful to those who wish to use simulation for training and education e.g., flight simulations. They also make use of games engines, a good platform for development and play.

Virtual Reality (VR): The use of computers, software and I/O devices to create an artificial environment that immerses the user in such a way that the user ‘believes’ the environment is real and is also known as a virtual environment. Although all of the 5 senses may be involved in computerized environments it is primarily sight, sound and touch (haptics) that are engaged.

Visualization: There are many definitions of visualization. For the purpose of this chapter we use the term to cover the use of computer and computer graphics technology to present data in a way that aids human understanding and communication. Today visualization is somewhat arbitrarily divided into scientific and information visualization.

Visual Analytics: Provides visual interfaces to large repositories of data by combining information visualization with human factors and data analysis to support decision making.

Scientific Visualization: The first distinct area of visualization to have developed. Initially computer graphics technology was used to ‘view’ the result of computer simulations which had an inherent geometry e.g., the flow of air over an aircraft.

Data Visualization: The second area of visualization to emerge that focused on statistical plots and thematic cartography. This area of visualization has now merged with information visualization.

Exploratory visualization: This term is not universally recognized in visualization, but the ideas covered by the term are important to this chapter. Exploratory visualization is an open process where the user has no set goal and/or is looking for no particular outcome – their intention is to understand their data better and perhaps to satisfy their curiosity. Researchers new to visualization often want to explore the data in an open way, to understand the possibilities and limitations of the technology. Alternatively researchers with results that are ‘unexpected’ may wish to use a number of techniques including visualization to investigate the ‘unexpected’ element of their science. These ‘unexpected’ results can potentially drive paradigm shifts in the science and must be carefully handled.

Information Visualization: The final area of visualization to emerge that initially aimed to show visually the relationships within databases i.e., information held in a database that has no geometrical or geographical association.

Haptics: Relates to touch and in this chapter applies to VR where a number of physical haptic devices exist; haptic rendering defines how a device is perceived.