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020 _a9783030243678
_9978-3-030-24367-8
024 7 _a10.1007/978-3-030-24367-8
_2doi
050 4 _aQA76.9.A73
072 7 _aUN
_2bicssc
072 7 _aCOM021000
_2bisacsh
072 7 _aUN
_2thema
082 0 4 _a005.72
_223
100 1 _aEarnshaw, Rae.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aData Science and Visual Computing
_h[electronic resource] /
_cby Rae Earnshaw, John Dill, David Kasik.
250 _a1st ed. 2019.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2019.
300 _aXVIII, 108 p. 16 illus., 11 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringerBriefs in Advanced Information and Knowledge Processing,
_x2524-5201
505 0 _aData Science -- Big Data -- Visual Computing -- Visualization -- Geometric Visualization -- Visual Analytics -- Data Science Institutes and Data Centers.
520 _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.
650 0 _aInformation retrieval.
650 0 _aComputer architecture.
650 0 _aComputer graphics.
650 0 _aUser interfaces (Computer systems).
650 0 _aHuman-computer interaction.
650 1 4 _aData Storage Representation.
650 2 4 _aComputer Graphics.
650 2 4 _aUser Interfaces and Human Computer Interaction.
700 1 _aDill, John.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
700 1 _aKasik, David.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783030243661
776 0 8 _iPrinted edition:
_z9783030243685
830 0 _aSpringerBriefs in Advanced Information and Knowledge Processing,
_x2524-5201
856 4 0 _uhttps://doi.org/10.1007/978-3-030-24367-8
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
942 _cSPRINGER
999 _c173885
_d173885