Handbook on data management in information systems
Author(s)
Bibliographic Information
Handbook on data management in information systems
(International handbooks on information systems)
Springer, 2003
Available at 8 libraries
  Aomori
  Iwate
  Miyagi
  Akita
  Yamagata
  Fukushima
  Ibaraki
  Tochigi
  Gunma
  Saitama
  Chiba
  Tokyo
  Kanagawa
  Niigata
  Toyama
  Ishikawa
  Fukui
  Yamanashi
  Nagano
  Gifu
  Shizuoka
  Aichi
  Mie
  Shiga
  Kyoto
  Osaka
  Hyogo
  Nara
  Wakayama
  Tottori
  Shimane
  Okayama
  Hiroshima
  Yamaguchi
  Tokushima
  Kagawa
  Ehime
  Kochi
  Fukuoka
  Saga
  Nagasaki
  Kumamoto
  Oita
  Miyazaki
  Kagoshima
  Okinawa
  Korea
  China
  Thailand
  United Kingdom
  Germany
  Switzerland
  France
  Belgium
  Netherlands
  Sweden
  Norway
  United States of America
Description and Table of Contents
Description
The Handbook provides practitioners, scientists and graduate students with a good overview of basic notions, methods and techniques, as well as important issues and trends across the broad spectrum of data management. In particular, the book covers fundamental topics in the field such as distributed databases, parallel databases, advanced databases, object-oriented databases, advanced transaction management, workflow management, data warehousing, data mining, mobile computing, data integration and the Web. Summing up, the Handbook is a valuable source of information for academics and practitioners who are interested in learning the key ideas in the considered area.
Table of Contents
1. Management of Data: State-of-the-Art and Emerging Trends.- 1 Introduction.- 2 Survey of the Volume.- 2. Database Systems: from File Systems to Modern Database Systems.- 1 Introduction - Database Concepts.- 2 Database System Generations.- 3 Network Database Systems.- 4 Hierarchical Database Systems.- 5 Relational Database Systems.- 6 Object-Oriented Database Systems.- 7 Federated, Mediated Database Systems and Data Warehouses.- 8 Conclusions.- 3. Data Modeling.- 1 Introduction.- 2 Early Concerns in Data Management.- 3 Abstraction in Data Modeling.- 4 Semantic Data Models.- 5 Models of Reality and Perception.- 6 Toward Cognition-Based Data Management.- 7 A Cognitive Approach to Data Modeling.- 8 Research Directions.- 4. Object-Oriented Database Systems.- 1 Introduction and Motivation.- 2 Object-Oriented Data Modeling.- 3 The Query Language OQL.- 4 Physical Object Management.- 5 Architecture of Client-Server-Systems.- 6 Indexing.- 7 Dealing with Set-Valued Attributes.- 8 Query Optimization.- 9 Conclusion.- 5. High Performance Parallel Database Management Systems.- 1 Introduction.- 2 Partitioning Strategies.- 3 Join Using Inter-Operator Parallelism.- 4 ORE: a Framework for Data Migration.- 5 Conclusions and Future Research Directions.- 6. Advanced Database Systems.- 1 Introduction.- 2 Preliminaries.- 3 Data Models and Modeling for Complex Objects.- 4 Advanced Query Languages.- 5 Advanced Database Server Capabilities.- 6 Conclusions and Outlook.- 7. Parallel and Distributed Multimedia Database Systems.- 1 Introduction.- 2 Media Fundamentals.- 3 MPEG as an Example of Media Compression.- 4 Organisation and Retrieval of Multimedia Data.- 5 Data Models for Multimedia Data.- 6 Multimedia Retrieval Sequence Using Images as an Example.- 7 Requirements for Multimedia Applications.- 8 Parallel and Distributed Processing of Multimedia Data.- 9 Parallel and Distributed Techniques for Multimedia Databases.- 10 Case Study: Cairo - Cluster Architecture for Image Retrieval and Organisation.- 11 Conclusions.- 8. Workflow Technology: the Support for Collaboration.- 1 Introduction.- 2 Application Scenario and Collaboration Requirements.- 3 Commercial Technologies Addressing Collaboration Requirements.- 4 Evaluation of Current Workflow Management Technology.- 5 Research Problems, Related Work, and Directions.- 6 Summary.- 9. Data Warehouses.- 1 Introduction.- 2 Basics.- 3 The Database of a Data Warehouse.- 4 The Data Warehouse Concept.- 5 Data Analysis of a Data Warehouse.- 6 Building a Data Warehouse.- 7 Future Research Directions.- 8 Conclusions.- 10. Mobile Computing.- 1 Introduction.- 2 Mobile Computing Infrastructure.- 3 Mobile Computing Software Architectures and Models.- 4 Disconnected Operation.- 5 Weak Connectivity.- 6 Data Delivery by Broadcast.- 7 Mobile Computing Resources and Pointers.- 8 Conclusions.- 11. Data Mining.- 1 Introduction.- 2 Mining Associations.- 3 Classification and Prediction.- 4 Clustering.- 5 Conclusions.- List of Contributors.
by "Nielsen BookData"