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010   $a3-030-24367-2
024 7 $a10.1007/978-3-030-24367-8
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035   $a(MiAaPQ)EBC5888544
035   $a(DE-He213)978-3-030-24367-8
035   $a(PPN)258851139
035   $a(EXLCZ)994100000009152816
100   $a20190814d2019      u|         0
101 0 $aeng
135   $aurcnu||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aData Science and Visual Computing /$fby Rae Earnshaw, John Dill, David Kasik
205   $a1st ed. 2019.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2019.
215   $a1 online resource (122 pages)
225 1 $aSpringerBriefs in Advanced Information and Knowledge Processing,$x2524-5201
311 08$a3-030-24366-4 
327   $aData Science -- Big Data -- Visual Computing -- Visualization -- Geometric Visualization -- Visual Analytics -- Data Science Institutes and Data Centers.
330   $aData science addresses the need to extract knowledge and information from data volumes, often from real-time sources in a wide variety of disciplines such as astronomy, bioinformatics, engineering, science, medicine, social science, business, and the humanities. The range and volume of data sources has increased enormously over time, particularly those generating real-time data. This has posed additional challenges for data management and data analysis of the data and effective representation and display. A wide range of application areas are able to benefit from the latest visual tools and facilities. Rapid analysis is needed in areas where immediate decisions need to be made. Such areas include weather forecasting, the stock exchange, and security threats. In areas where the volume of data being produced far exceeds the current capacity to analyze all of it, attention is being focussed how best to address these challenges. Optimum ways ofaddressing large data sets across a variety of disciplines have led to the formation of national and institutional Data Science Institutes and Centers. Being driven by national priority, they are able to attract support for research and development within their organizations and institutions to bring together interdisciplinary expertise to address a wide variety of problems. Visual computing is a set of tools and methodologies that utilize 2D and 3D images to extract information from data. Such methods include data analysis, simulation, and interactive exploration. These are analyzed and discussed.
410  0$aSpringerBriefs in Advanced Information and Knowledge Processing,$x2524-5201
606   $aInformation retrieval
606   $aComputer architecture
606   $aComputer graphics
606   $aUser interfaces (Computer systems)
606   $aHuman-computer interaction
606   $aData Storage Representation
606   $aComputer Graphics
606   $aUser Interfaces and Human Computer Interaction
615  0$aInformation retrieval.
615  0$aComputer architecture.
615  0$aComputer graphics.
615  0$aUser interfaces (Computer systems).
615  0$aHuman-computer interaction.
615 14$aData Storage Representation.
615 24$aComputer Graphics.
615 24$aUser Interfaces and Human Computer Interaction.
676   $a621.367
676   $a621.367
700   $aEarnshaw$b Rae A.$f1944-$4aut$4http://id.loc.gov/vocabulary/relators/aut$0772220
702   $aDill$b John$4aut$4http://id.loc.gov/vocabulary/relators/aut
702   $aKasik$b David$4aut$4http://id.loc.gov/vocabulary/relators/aut
906   $aBOOK
912   $a9910349285703321
996   $aData Science and Visual Computing$93397089
997   $aUNINA