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...
Gespeichert in:
| Hauptverfasser: | , , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Cham
Springer
[2019]
|
| Schriftenreihe: | Advanced information and knowledge processing
Springer briefs in advanced information and knowledge processing |
| Schlagworte: | |
| Zusammenfassung: | 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 |
| Beschreibung: | Enthält Literaturangaben |
| Beschreibung: | xviii, 108 Seiten Illustrationen, Diagramme |
| ISBN: | 9783030243661 |
Internformat
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| 500 | |a Enthält Literaturangaben | ||
| 505 | 8 | |a Data Science -- Big Data -- Visual Computing -- Visualization -- Geometric Visualization -- Visual Analytics -- Data Science Institutes and Data Centers | |
| 520 | |a 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 | ||
| 650 | 4 | |a Computer science | |
| 650 | 4 | |a Computer graphics | |
| 653 | 0 | |a Data Storage Representation / http://scigraph.springernature.com/things/product-market-codes/I15025 | |
| 653 | 0 | |a Computer Graphics / http://scigraph.springernature.com/things/product-market-codes/I22013 | |
| 653 | 0 | |a User Interfaces and Human Computer Interaction / http://scigraph.springernature.com/things/product-market-codes/I18067 | |
| 700 | 1 | |a Dill, John |d 1939- |e Verfasser |0 (DE-588)1100918957 |4 aut | |
| 700 | 1 | |a Kasik, David |e Verfasser |4 aut | |
| 776 | 0 | 8 | |i Erscheint auch als |n Online-Ausgabe |z 978-3-030-24367-8 |
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Datensatz im Suchindex
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| author | Earnshaw, Rae A. 1944- Dill, John 1939- Kasik, David |
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| author_facet | Earnshaw, Rae A. 1944- Dill, John 1939- Kasik, David |
| author_role | aut aut aut |
| author_sort | Earnshaw, Rae A. 1944- |
| author_variant | r a e ra rae j d jd d k dk |
| building | Verbundindex |
| bvnumber | BV047322021 |
| callnumber-first | Q - Science |
| callnumber-label | QA76 |
| callnumber-raw | QA76.9.D35 |
| callnumber-search | QA76.9.D35 |
| callnumber-sort | QA 276.9 D35 |
| callnumber-subject | QA - Mathematics |
| classification_rvk | QH 500 |
| contents | Data Science -- Big Data -- Visual Computing -- Visualization -- Geometric Visualization -- Visual Analytics -- Data Science Institutes and Data Centers |
| ctrlnum | (DE-599)OBVAC15476945 |
| dewey-full | 004.5 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 004 - Computer science |
| dewey-raw | 004.5 |
| dewey-search | 004.5 |
| dewey-sort | 14.5 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik Wirtschaftswissenschaften |
| discipline_str_mv | Informatik Wirtschaftswissenschaften |
| format | Book |
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| id | DE-604.BV047322021 |
| illustrated | Illustrated |
| index_date | 2024-07-03T17:29:37Z |
| indexdate | 2024-07-10T09:08:51Z |
| institution | BVB |
| isbn | 9783030243661 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-032724749 |
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| owner | DE-11 |
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| physical | xviii, 108 Seiten Illustrationen, Diagramme |
| publishDate | 2019 |
| publishDateSearch | 2019 |
| publishDateSort | 2019 |
| publisher | Springer |
| record_format | marc |
| series2 | Advanced information and knowledge processing Springer briefs in advanced information and knowledge processing |
| spelling | Earnshaw, Rae A. 1944- Verfasser (DE-588)172058309 aut Data science and visual computing Rae Earnshaw, John Dill, David Kasik Cham Springer [2019] © 2019 xviii, 108 Seiten Illustrationen, Diagramme txt rdacontent n rdamedia nc rdacarrier Advanced information and knowledge processing Springer briefs in advanced information and knowledge processing Enthält Literaturangaben 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 Computer science Computer graphics Data Storage Representation / http://scigraph.springernature.com/things/product-market-codes/I15025 Computer Graphics / http://scigraph.springernature.com/things/product-market-codes/I22013 User Interfaces and Human Computer Interaction / http://scigraph.springernature.com/things/product-market-codes/I18067 Dill, John 1939- Verfasser (DE-588)1100918957 aut Kasik, David Verfasser aut Erscheint auch als Online-Ausgabe 978-3-030-24367-8 |
| spellingShingle | Earnshaw, Rae A. 1944- Dill, John 1939- Kasik, David Data science and visual computing Data Science -- Big Data -- Visual Computing -- Visualization -- Geometric Visualization -- Visual Analytics -- Data Science Institutes and Data Centers Computer science Computer graphics |
| title | Data science and visual computing |
| title_auth | Data science and visual computing |
| title_exact_search | Data science and visual computing |
| title_exact_search_txtP | Data science and visual computing |
| title_full | Data science and visual computing Rae Earnshaw, John Dill, David Kasik |
| title_fullStr | Data science and visual computing Rae Earnshaw, John Dill, David Kasik |
| title_full_unstemmed | Data science and visual computing Rae Earnshaw, John Dill, David Kasik |
| title_short | Data science and visual computing |
| title_sort | data science and visual computing |
| topic | Computer science Computer graphics |
| topic_facet | Computer science Computer graphics |
| work_keys_str_mv | AT earnshawraea datascienceandvisualcomputing AT dilljohn datascienceandvisualcomputing AT kasikdavid datascienceandvisualcomputing |