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Published by LAP LAMBERT Academic Publishing, 2012
ISBN 10: 3659256862 ISBN 13: 9783659256868
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Published by LAP LAMBERT Academic Publishing, 2012
ISBN 10: 3659256862 ISBN 13: 9783659256868
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Taschenbuch. Condition: Neu. Challenges in Scientific Data Management | What's New in Scientific Data to DBMS: Challenges, Features, and Optimizations | Mohamed Eltabakh | Taschenbuch | 180 S. | Englisch | 2012 | LAP LAMBERT Academic Publishing | EAN 9783659256868 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.
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Published by Chapman and Hall/CRC, 2019
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Taschenbuch. Condition: Neu. Scientific Data Management | Challenges, Technology, and Deployment | Arie Shoshani (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2019 | Chapman and Hall/CRC | EAN 9780367384760 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.
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Condition: Sehr gut. Zustand: Sehr gut | Seiten: 590 | Sprache: Englisch | Produktart: Bücher | This work describes cutting-edge technologies and solutions for managing and analyzing vast amounts of scientific data. It begins with coverage of efficient storage systems, discussing how to write and read large volumes of data without slowing the simulation, analysis, or visualization processes. The book then focuses on the efficient data movement and management of storage spaces and explores emerging database systems for scientific data. It also addresses how to best organize data for analysis purposes, how to effectively conduct searches over large datasets, how to successfully automate multistep scientific process workflows, and how to automatically collect metadata and lineage information.
Language: English
Published by Taylor & Francis Ltd, 2019
ISBN 10: 0367384760 ISBN 13: 9780367384760
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Condition: Hervorragend. Zustand: Hervorragend | Seiten: 590 | Sprache: Englisch | Produktart: Bücher | This work describes cutting-edge technologies and solutions for managing and analyzing vast amounts of scientific data. It begins with coverage of efficient storage systems, discussing how to write and read large volumes of data without slowing the simulation, analysis, or visualization processes. The book then focuses on the efficient data movement and management of storage spaces and explores emerging database systems for scientific data. It also addresses how to best organize data for analysis purposes, how to effectively conduct searches over large datasets, how to successfully automate multistep scientific process workflows, and how to automatically collect metadata and lineage information.
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Published by Chapman and Hall/CRC, 2009
ISBN 10: 1420069802 ISBN 13: 9781420069808
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Published by Chapman and Hall/CRC, 2009
ISBN 10: 1420069802 ISBN 13: 9781420069808
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Published by Taylor & Francis Ltd, 2009
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Published by LAP LAMBERT Academic Publishing Okt 2012, 2012
ISBN 10: 3659256862 ISBN 13: 9783659256868
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The growth of scientific information and the increasing automation of data collection have made databases integral to many scientific disciplines including life sciences, physics, meteorology, and chemistry. These sciences pose new data management challenges to current DBMSs. This book addresses three key challenges in scientific data management: (1) Annotation Management: Annotations are important metadata that go hand-in-hand with scientific data. However, a major challenge is how to manage large volumes of annotations along with their corresponding data items. (2) Complex Dependencies Involving Real-world Activities: The processing of scientific data is complex and may involve sequences of activities external to the database system, e.g., wet-lab experiments, and manual measurements. The challenge is how to efficiently integrate these activities within the database engine. And (3) Fast Access to Scientific Data: Scientific experiments produce large volumes of data of complex types, e.g., arrays, images, and long sequences. A major challenge is how to provide fast access to these large pools of scientific data with non-traditional data types. 180 pp. Englisch.
Language: English
Published by LAP LAMBERT Academic Publishing, 2012
ISBN 10: 3659256862 ISBN 13: 9783659256868
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Eltabakh MohamedIs an Assistant Professor of computer science at Worcester Polytechnic Institute. His research interest is in the broad area of Database Management Systems and Information Management. His work is in the areas of query.
Language: English
Published by Chapman and Hall/CRC, 2019
ISBN 10: 0367384760 ISBN 13: 9780367384760
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Published by LAP LAMBERT Academic Publishing, 2012
ISBN 10: 3659256862 ISBN 13: 9783659256868
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Published by LAP LAMBERT Academic Publishing, 2012
ISBN 10: 3659256862 ISBN 13: 9783659256868
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Published by LAP LAMBERT Academic Publishing Okt 2012, 2012
ISBN 10: 3659256862 ISBN 13: 9783659256868
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The growth of scientific information and the increasing automation of data collection have made databases integral to many scientific disciplines including life sciences, physics, meteorology, and chemistry. These sciences pose new data management challenges to current DBMSs. This book addresses three key challenges in scientific data management: (1) Annotation Management: Annotations are important metadata that go hand-in-hand with scientific data. However, a major challenge is how to manage large volumes of annotations along with their corresponding data items. (2) Complex Dependencies Involving Real-world Activities: The processing of scientific data is complex and may involve sequences of activities external to the database system, e.g., wet-lab experiments, and manual measurements. The challenge is how to efficiently integrate these activities within the database engine. And (3) Fast Access to Scientific Data: Scientific experiments produce large volumes of data of complex types, e.g., arrays, images, and long sequences. A major challenge is how to provide fast access to these large pools of scientific data with non-traditional data types.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 180 pp. Englisch.