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    Object Relationship Notation (ORN) for Database Applications

Object Relationship Notation (ORN) for Database Applications

Bryon K. Ehlmann
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      Conceptually, a database consists of objects and relationships. Object Relationship Notation (ORN) is a simple notation that more precisely defines relationships by combining UML multiplicities with uniquely defined referential actions.This book shows how ORN can be used in UML class diagrams and database definition languages (DDLs) to better model and implement relationships and thus more productively develop database applications. For the database developer, it presents many examples of relationships modeled using ORN-extended class diagrams and shows how these relationships are easily mapped to an ORN-extended SQL or Object DDL. For the DBMS developer, it presents the specifications and algorithms needed to implement ORN in a relational and object DBMS.  This book also describes tools that can be downloaded or accessed via the Web.  These tools allow databases to be modeled using ORN and implemented using automatic code generation that adds ORN support to Microsoft SQL Server and Progress Object Store.Object Relationship Notation (ORN) for Database Applications:  Enhancing the Modeling and Implementation of Associations is written for research scientists, research libraries, professionals, and advanced-level students in computer science. 
      Format: CONTRIBUTORS: Bryon K. Ehlmann EAN: 9780387095530 COUNTRY: United States PAGES: WEIGHT: 1230 g HEIGHT: 235 cm
      PUBLISHED BY: Springer-Verlag New York Inc. DATE PUBLISHED: 2009-06-22 CITY: GENRE: COMPUTERS / Artificial Intelligence / Computer Vision & Pattern Recognition, COMPUTERS / Database Administration & Management, COMPUTERS / Data Science / Data Analytics, COMPUTERS / System Administration / Storage & Retrieval, COMPUTERS / Information Theory WIDTH: 155 cm SPINE:

      Book Themes:

      Information theory, Algorithms and data structures, Databases, Data warehousing, Data mining, Information retrieval, Artificial intelligence, Expert systems / knowledge-based systems, Image processing

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      Conceptually, a database consists of objects and relationships. Object Relationship Notation (ORN) is a simple notation that more precisely defines relationships by combining UML multiplicities with uniquely defined referential actions.This book shows how ORN can be used in UML class diagrams and database definition languages (DDLs) to better model and implement relationships and thus more productively develop database applications. For the database developer, it presents many examples of relationships modeled using ORN-extended class diagrams and shows how these relationships are easily mapped to an ORN-extended SQL or Object DDL. For the DBMS developer, it presents the specifications and algorithms needed to implement ORN in a relational and object DBMS.  This book also describes tools that can be downloaded or accessed via the Web.  These tools allow databases to be modeled using ORN and implemented using automatic code generation that adds ORN support to Microsoft SQL Server and Progress Object Store.Object Relationship Notation (ORN) for Database Applications:  Enhancing the Modeling and Implementation of Associations is written for research scientists, research libraries, professionals, and advanced-level students in computer science. 
      Format: CONTRIBUTORS: Bryon K. Ehlmann EAN: 9780387095530 COUNTRY: United States PAGES: WEIGHT: 1230 g HEIGHT: 235 cm
      PUBLISHED BY: Springer-Verlag New York Inc. DATE PUBLISHED: 2009-06-22 CITY: GENRE: COMPUTERS / Artificial Intelligence / Computer Vision & Pattern Recognition, COMPUTERS / Database Administration & Management, COMPUTERS / Data Science / Data Analytics, COMPUTERS / System Administration / Storage & Retrieval, COMPUTERS / Information Theory WIDTH: 155 cm SPINE:

      Book Themes:

      Information theory, Algorithms and data structures, Databases, Data warehousing, Data mining, Information retrieval, Artificial intelligence, Expert systems / knowledge-based systems, Image processing

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