Data Science and Visual Computing

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.

Data Science and Visual Computing

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.

More Books:

Data Science and Visual Computing
Language: en
Pages: 108
Authors: Rae Earnshaw, John Dill, David Kasik
Categories: Computers
Type: BOOK - Published: 2019-08-30 - Publisher: Springer Nature

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
Data Science and Visual Computing
Language: en
Pages: 108
Authors: Rae Earnshaw, John Dill, David Kasik
Categories: Computers
Type: BOOK - Published: 2019-08-24 - Publisher: Springer

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
Data Science for Healthcare
Language: en
Pages: 367
Authors: Sergio Consoli, Diego Reforgiato Recupero, Milan Petković
Categories: Computers
Type: BOOK - Published: 2019-02-23 - Publisher: Springer

This book seeks to promote the exploitation of data science in healthcare systems. The focus is on advancing the automated analytical methods used to extract new knowledge from data for healthcare applications. To do so, the book draws on several interrelated disciplines, including machine learning, big data analytics, statistics, pattern
Soft Computing in Data Science
Language: en
Pages: 388
Authors: Michael W. Berry, Bee Wah Yap, Azlinah Mohamed, Mario Köppen
Categories: Computers
Type: BOOK - Published: 2019-09-23 - Publisher: Springer Nature

This book constitutes the refereed proceedings of the 5th International Conference on Soft Computing in Data Science, SCDS 2019, held in Iizuka, Japan, in August 2019. The 30 revised full papers presented were carefully reviewed and selected from 75 submissions. The papers are organized in topical sections on ​information and
Social Big Data Analytics
Language: en
Pages: 218
Authors: Bilal Abu-Salih, Pornpit Wongthongtham, Dengya Zhu, Kit Yan Chan, Amit Rudra
Categories: Business & Economics
Type: BOOK - Published: 2021-03-10 - Publisher: Springer Nature

This book focuses on data and how modern business firms use social data, specifically Online Social Networks (OSNs) incorporated as part of the infrastructure for a number of emerging applications such as personalized recommendation systems, opinion analysis, expertise retrieval, and computational advertising. This book identifies how in such applications, social