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Data science and visual computing

Dill, John.

Data science and visual computing

Record Type:	Electronic resources : Monograph/item
Title/Author:	Data science and visual computingby Rae Earnshaw, John Dill, David Kasik.
Author:	Earnshaw, Rae.
other author:	Dill, John.
Published:	Cham :Springer International Publishing :2019.
Description:	xviii, 108 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Optical data processing.
Online resource:	https://doi.org/10.1007/978-3-030-24367-8
ISBN:	9783030243678$q(electronic bk.)

Data science and visual computing
Earnshaw, Rae.

Data science and visual computing[electronic resource] /by Rae Earnshaw, John Dill, David Kasik. - Cham :Springer International Publishing :2019. - xviii, 108 p. :ill., digital ;24 cm. - SpringerBriefs in advanced information and knowledge processing,2524-5198. - SpringerBriefs in advanced information and knowledge processing..

Data Science -- Big Data -- Visual Computing -- Visualization -- Geometric Visualization -- Visual Analytics -- Data Science Institutes and Data Centers.

Data science addresses the need to extract knowledge and information from data volumes, often from real-time sources in a wide variety of disciplines such as astronomy, bioinformatics, engineering, science, medicine, social science, business, and the humanities. The range and volume of data sources has increased enormously over time, particularly those generating real-time data. This has posed additional challenges for data management and data analysis of the data and effective representation and display. A wide range of application areas are able to benefit from the latest visual tools and facilities. Rapid analysis is needed in areas where immediate decisions need to be made. Such areas include weather forecasting, the stock exchange, and security threats. In areas where the volume of data being produced far exceeds the current capacity to analyze all of it, attention is being focussed how best to address these challenges. Optimum ways of addressing large data sets across a variety of disciplines have led to the formation of national and institutional Data Science Institutes and Centers. Being driven by national priority, they are able to attract support for research and development within their organizations and institutions to bring together interdisciplinary expertise to address a wide variety of problems. Visual computing is a set of tools and methodologies that utilize 2D and 3D images to extract information from data. Such methods include data analysis, simulation, and interactive exploration. These are analyzed and discussed.

ISBN: 9783030243678$q(electronic bk.)

Standard No.: 10.1007/978-3-030-24367-8doiSubjects--Topical Terms:

185609
Optical data processing.

LC Class. No.: TA1630 / .E37 2019

Dewey Class. No.: 621.367

Data science and visual computing
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