scientific visualisation, is an interdisciplinary field within science aimed at the graphical representation of scientific phenomena. It is a branch of computer graphics and computer science, focused on using visual interfaces to make scientific data comprehensible and accessible for scientific analysis. Current research in how visualizations are interpreted helps identify the most effective types and features for conveying complex scientific information. More on visualization research, Additional studies.
One of the first instances of three-dimensional scientific visualization was Maxwell's thermodynamic surface, modeled in clay by James Clerk Maxwell in 1874, which anticipated the use of computer graphics in scientific visualization today. Read about Maxwell's visualization.
Data visualization in scientific contexts is classified based on the dimension of the data and the methods used. These methods include:
As computer graphics evolved, scientific visualization became increasingly popular for displaying both simulated and measured data. This section focuses on the primary visualization techniques for two-dimensional (2D) data sets.
2D tensor fields often require decomposition into vector fields for visualization. This is typically achieved by:
Three-dimensional (3D) data visualization techniques vary depending on the nature of the data being visualized. Here, we explore methods for scalar fields, vector fields, and tensor fields.
Computer animation combines art, technique, and science to create moving images through computers. While modern animations are increasingly created using 3D computer graphics, 2D graphics remain prevalent due to their stylistic appeal, lower bandwidth demands, and faster rendering capabilities suitable for real-time applications. The final output of computer animations can be aimed at various platforms, including digital interfaces and traditional film media.
Often referred to as CGI, computer-generated imagery is extensively used in the film industry to create visual effects that are either impractical or impossible to achieve through traditional filming techniques. CGI encompasses both dynamic video sequences and static scene visualizations.
Computer simulation involves a program or network of computers that replicates an abstract model of a particular system. These simulations are integral to mathematical modeling across various fields such as physics, chemistry, biology, economics, psychology, social science, and engineering. The goal is to gain insights into how these systems operate or to observe their behavior under different conditions.
Computer simulations are utilized to model natural systems in scientific fields such as physics (computational physics), chemistry, and biology, as well as human systems in economics, psychology, and social sciences. In engineering and technology development, simulations assist in the design and optimization processes, providing critical insights that guide decision-making and innovation.
The complexity of computer simulations can vary widely. They might run for just a few minutes on a single computer or for hours on networked groups of computers. Some simulations are even more extensive, running continuously for months on supercomputers. For example, over a decade ago, a military simulation of a desert battle involved modeling 66,239 tanks, trucks, and other vehicles on a simulated terrain around Kuwait, utilizing multiple supercomputers as part of the DoD High Performance Computing Modernization Program.
Information visualization is the study and practice of visually representing large-scale collections of non-numerical information, such as files and lines of code in software systems, library and bibliographic databases, networks of relations on the internet, and other similar data sources.
The focus of information visualization is to develop methods that convey abstract information in intuitive visual formats. By leveraging visual representations and interaction techniques, information visualization utilizes the human eye’s broad bandwidth pathway to the mind, enabling users to see, explore, and understand large volumes of information simultaneously. This approach is particularly effective in making complex data accessible and comprehensible.
Unlike scientific visualization, which is primarily concerned with numerical data generated through scientific research, information visualization applies to a broader spectrum of data. This field is often utilized in contexts outside of scientific inquiry, including business, government, news, and social media applications.
Information visualization is instrumental in creating graphical representations that help in decision-making and communication across various sectors. For instance, it enables the visualization of data trends in business, patterns of interaction in social media, or demographic information for government policies.
Explore more about information visualization and its applications.
Interface technology and perception explore how innovative interfaces and an enhanced understanding of perceptual challenges open new possibilities for the scientific visualization community. This advancement allows for more intuitive and effective ways to interact with and visualize scientific data, fostering deeper insights and broader applications.
Rendering is the process of generating an image from a model using computer programs. This model typically contains detailed descriptions of 3D objects, including their geometry, viewpoint, texture, lighting, and shading information. The term "rendering" might be likened to an "artist's rendering" of a scene, as it involves creating a visual output from structured data.
These rendering techniques are crucial in computer graphics for creating realistic and engaging visuals, significantly impacting video production, gaming, simulations, and scientific visualization.
Volume rendering is a technique used to display a 2D projection of a 3D discretely sampled data set. This technique is often applied to data from CT or MRI scans, which typically consist of a series of 2D slice images. These slices are usually captured in a consistent pattern, such as one slice per millimeter, and form a regular volumetric grid. Each volume element, or voxel, in this grid represents a single value obtained by sampling the area around it.
Volume visualization is a set of techniques used for viewing three-dimensional data sets without the need to mathematically define their surfaces. Initially crucial in medical imaging, this technique has broadened to include applications in multiple scientific fields, such as meteorology, oceanography, and molecular biology, where it helps illustrate complex phenomena like cloud formations, water flows, and cellular structures. However, many volume visualization algorithms require significant computational power and data storage. Recent advances in hardware and software have enhanced the capabilities and performance of volume visualization, making it more accessible and feasible for real-time applications.
Developments in web technologies and in-browser rendering have facilitated more straightforward volumetric presentations. These technologies enable interactive visualization of cuboids in a changing frame of reference, effectively demonstrating volume, mass, and density data.
Main article: Mathematical visualization
Mathematical visualization aids in forming mental models and building intuition about mathematical structures: