000 | 03904nam a22005775i 4500 | ||
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001 | 978-3-030-24367-8 | ||
003 | DE-He213 | ||
005 | 20240423125052.0 | ||
007 | cr nn 008mamaa | ||
008 | 190814s2019 sz | s |||| 0|eng d | ||
020 |
_a9783030243678 _9978-3-030-24367-8 |
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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. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
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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 |