Computational science in the context of "Supercomputer"

Geographic information science (GIScience, GISc) or geoinformation science is a scientific discipline at the crossroads of computational science, social science, and natural science that studies geographic information, including how it represents phenomena in the real world, how it represents the way humans understand the world, and how it can be captured, organized, and analyzed. It is a sub-field of geography, specifically part of technical geography. It has applications to both physical geography and human geography, although its techniques can be applied to many other fields of study as well as many different industries.

As a field of study or profession, it can be contrasted with geographic information systems (GIS), which are the actual repositories of geospatial data, the software tools for carrying out relevant tasks, and the profession of GIS users. That said, one of the major goals of GIScience is to find practical ways to improve GIS data, software, and professional practice; it is more focused on how GIS is applied in real life as opposed to being a geographic information system tool in and of itself. The field is also sometimes called geographical information science.

The Mathematical Sciences are a group of areas of study that includes, in addition to mathematics, those academic disciplines that are primarily mathematical in nature but may not be universally considered subfields of mathematics proper.

Statistics, for example, is mathematical in its methods but grew out of bureaucratic and scientific observations, which merged with inverse probability and then grew through applications in some areas of physics, biometrics, and the social sciences to become its own separate, though closely allied, field. Theoretical astronomy, theoretical physics, theoretical and applied mechanics, continuum mechanics, mathematical chemistry, actuarial science, computer science, computational science, data science, operations research, quantitative biology, control theory, econometrics, geophysics and mathematical geosciences are likewise other fields often considered part of the mathematical sciences.

Computational statistics, or statistical computing, is the study which is the intersection of statistics and computer science, and refers to the statistical methods that are enabled by using computational methods. It is the area of computational science (or scientific computing) specific to the mathematical science of statistics. This area is fast developing. The view that the broader concept of computing must be taught as part of general statistical education is gaining momentum.

As in traditional statistics the goal is to transform raw data into knowledge, but the focus lies on computer intensive statistical methods, such as cases with very large sample size and non-homogeneous data sets.

A workstation is a special computer designed for technical or scientific applications. Intended primarily to be used by a single user, they are commonly connected to a local area network and run multi-user operating systems. The term workstation has been used loosely to refer to everything from a mainframe computer terminal to a PC connected to a network, but the most common form refers to the class of hardware offered by several current and defunct companies such as Sun Microsystems, Silicon Graphics, Apollo Computer, DEC, HP, NeXT, and IBM which powered the 3D computer graphics revolution of the late 1990s.

Workstations formerly offered higher performance specifications than mainstream personal computers, especially in terms of processing, graphics, memory, and multitasking. Workstations are optimized for the visualization and manipulation of different types of complex data such as 3D mechanical design, engineering simulations like computational fluid dynamics, animation, video editing, image editing, medical imaging, image rendering, computational science, generating mathematical plots, and software development. Typically, the form factor is that of a desktop computer, which consists of a high-resolution display, a keyboard, and a mouse at a minimum, but also offers multiple displays, graphics tablets, and 3D mice for manipulating objects and navigating scenes. Workstations were the first segment of the computer market to present advanced accessories, and collaboration tools like videoconferencing.

Machine perception is the capability of a computer system to interpret data in a manner that is similar to the way humans use their senses to relate to the world around them. The basic method that the computers take in and respond to their environment is through the attached hardware. Until recently input was limited to a keyboard, or a mouse, but advances in technology, both in hardware and software, have allowed computers to take in sensory input in a way similar to humans.

Machine perception allows the computer to use this sensory input, as well as conventional computational means of gathering information, to gather information with greater accuracy and to present it in a way that is more comfortable for the user. These include computer vision, machine hearing, machine touch, and machine smelling, as artificial scents are, at a chemical compound, molecular, atomic level, indiscernible and identical.

Computational anatomy is an interdisciplinary field of biology focused on quantitative investigation and modelling of anatomical shapes variability. It involves the development and application of mathematical, statistical and data-analytical methods for modelling and simulation of biological structures.

The field is broadly defined and includes foundations in anatomy, applied mathematics and pure mathematics, machine learning, computational mechanics, computational science, biological imaging, neuroscience, physics, probability, and statistics; it also has strong connections with fluid mechanics and geometric mechanics. Additionally, it complements newer, interdisciplinary fields like bioinformatics and neuroinformatics in the sense that its interpretation uses metadata derived from the original sensor imaging modalities (of which magnetic resonance imaging is one example). It focuses on the anatomical structures being imaged, rather than the medical imaging devices. It is similar in spirit to the history of computational linguistics, a discipline that focuses on the linguistic structures rather than the sensor acting as the transmission and communication media.

Information Processing and Management is a bimonthly peer-reviewed academic journal published by Elsevier covering the field of information and computational sciences applied to management. The journal was established in 1963 as Information Storage and Retrieval, obtaining its current name in 1975.