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Information Modeling and Relational Databases
- 2nd Edition - March 3, 2008
- Authors: Terry Halpin, Tony Morgan
- Language: English
- Hardback ISBN:9 7 8 - 0 - 1 2 - 3 7 3 5 6 8 - 3
- eBook ISBN:9 7 8 - 0 - 0 8 - 0 5 6 8 7 3 - 7
Information Modeling and Relational Databases, Second Edition, provides an introduction to ORM (Object-Role Modeling)and much more. In fact, it is the only book to go beyond in… Read more
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Request a sales quoteInformation Modeling and Relational Databases, Second Edition, provides an introduction to ORM (Object-Role Modeling)and much more. In fact, it is the only book to go beyond introductory coverage and provide all of the in-depth instruction you need to transform knowledge from domain experts into a sound database design. This book is intended for anyone with a stake in the accuracy and efficacy of databases: systems analysts, information modelers, database designers and administrators, and programmers.
Terry Halpin, a pioneer in the development of ORM, blends conceptual information with practical instruction that will let you begin using ORM effectively as soon as possible. Supported by examples, exercises, and useful background information, his step-by-step approach teaches you to develop a natural-language-based ORM model, and then, where needed, abstract ER and UML models from it. This book will quickly make you proficient in the modeling technique that is proving vital to the development of accurate and efficient databases that best meet real business objectives.
- Presents the most indepth coverage of Object-Role Modeling available anywhere, including a thorough update of the book for ORM2, as well as UML2 and E-R (Entity-Relationship) modeling
- Includes clear coverage of relational database concepts, and the latest developments in SQL and XML, including a new chapter on the impact of XML on information modeling, exchange and transformation
- New and improved case studies and exercises are provided for many topics
Data modelers, database designers, information architects, and practitioners/managers in data management
1 Introduction
1.1 Information Modeling
1.2 Modeling Approaches
1.3 Some Historical Background
1.4 The Relevant Skills
1.5 Summary
2 Information Levels and Frameworks
2.1 Four Information Levels
2.2 The Conceptual Level
2.3 Database Design Example
2.4 Development Frameworks
2.5 Summary
3 Conceptual Modeling: First Steps
3.1 Conceptual Modeling Language Criteria
3.2 Conceptual Schema Design Procedure
3.3 CSDP Step 1: From Examples to Elementary Facts
3.4 CSDP Step 2: Draw Fact Types, and Populate
3.5 CSDP Step 3: Trim Schema; Note Basic Derivations
3.6 Summary
4 Uniqueness Constraints
4.1 CSDP Step 4: Uniqueness Constraints; Arity Check
4.2 Uniqueness Constraints on Unaries and Binaries
4.3 Uniqueness Constraints on Longer Fact Types
4.4 External Uniqueness Constraints
4.5 Key Length Check
4.6 Projections and Joins
4.7 Summary
5 Mandatory Roles
5.1 Introduction to CSDP Step 5
5.2 Mandatory and Optional Roles
5.3 Reference Schemes
5.4 Case Study: A Compact Disc Retailer
5.5 Logical Derivation Check
5.6 Summary
6 Value, Set-Comparison and Subtype Constraints
6.1 CSDP Step 6: Value, Set-Comparison and Subtype constraints
6.2 Basic Set Theory
6.3 Value Constraints and Independent Objects
6.4 Subset, Equality, and Exclusion Constraints
6.5 Subtyping
6.6 Generalization of Object Types
6.7 Summary
7 Other Constraints and Final Checks
7.1 CSDP Step 7: Other Constraints and Final Checks
7.2 Occurrence Frequencies
7.3 Ring Constraints
7.4 Other Constraints and Rules
7.5 Final Checks
7.6 Summary
8 Entity Relationship Modeling
8.1 Overview of ER
8.2 Barker notation
8.3 Information Engineering notation
8.4 IDEF1X
8.5 Mapping from ORM to ER
8.6 Summary
9 Data Modeling in UML
9.1 Introduction
9.2 Object-Orientation
9.3 Attributes
9.4 Associations
9.5 Set-Comparison constraints
9.6 Subtyping
9.7 Other Constraints and Derivation Rules
9.8 Mapping from ORM to UML
9.9 Summary
10 Advanced Modeling Issues
10.1 Join Constraints
10.2 Deontic Rules
10.3 Temporality
10.4 Collection Types
10.5 Nominalization and Objectification
10.6 Open/Closed World Semantics
10.7 Higher-Order Types
10.8 Summary
11 Relational Mapping
11.1 Implementing a Conceptual Schema
11.2 Relational Schemas
11.3 Relational Mapping Procedure
11.4 Advanced Mapping Aspects
11.5 Summary
12 Data Manipulation with Relational Languages
12.1 Relational Algebra
12.2 Relational Database Systems
12.3 SQL: Historical and Structural Overview
12.4 SQL: Identifiers and Data Types
12.5 SQL: Choosing Columns, Rows, and Order
12.6 SQL: Joins
12.7 SQL: In, Between, Like, and Null Operators
12.8 SQL: Union and Simple Subqueries
12.9 SQL: Scalar Operators and Bag Functions
12.10 SQL: Grouping
12.11 SQL: Correlated and Existential Subqueries
12.12 SQL: Recursive Queries
12.13 SQL: Updating Table Populations
12.14 SQL: Other Useful Constructs
12.15 Summary
13 Using Other Database Objects
13.1 SQL: Data Definition
13.2 SQL: User Defined Functions
13.3 SQL: Views and Computed Columns
13.4 SQL: Triggers
13.5 SQL: Stored Procedures
13.6 SQL: Indexes
13.7 Other Objects
13.8 Exploiting 3GLs
13.9 Exploiting XML
13.10 Security and Meta-Data
13.11 Concurrency
13.12 Summary
14 Schema Transformations
14.1 Schema Equivalence and Optimization
14.2 Predicate Specialization and Generalization
14.3 Nesting, Coreferencing, and Flattening
14.4 Other Transformations
14.5 Conceptual Schema Optimization
14.6 Normalization
14.7 Denormalization and Low Level Optimization
14.8 Reengineering
14.9 Data Migration and Query Transformation
14.10 Summary
15 Process and State Modeling
15.1 Introduction
15.2 Processes and Workflow
15.3 Foundations for Process Theory
15.4 State Models versus Process Models
15.5 Modeling Information Dynamics in UML
15.6 Standard Process Patterns
15.7 Business Process Standards Initiatives
15.8 Integration of Process Models and Information Models
15.9 Summary
16 Other Modeling Aspects and Trends
16.1 Introduction
16.2 Data Warehousing and OLAP
16.3 Conceptual Query Languages
16.4 Schema Abstraction Mechanisms
16.5 Further Design Aspects
16.6 Ontologies and the Semantic Web
16.7 Post-Relational Databases
16.8 Metamodeling
16.9 Summary
ORM glossary (ORM 1 and ORM 2)
ER glossary
UML glossary
Bibliography
Index
1.1 Information Modeling
1.2 Modeling Approaches
1.3 Some Historical Background
1.4 The Relevant Skills
1.5 Summary
2 Information Levels and Frameworks
2.1 Four Information Levels
2.2 The Conceptual Level
2.3 Database Design Example
2.4 Development Frameworks
2.5 Summary
3 Conceptual Modeling: First Steps
3.1 Conceptual Modeling Language Criteria
3.2 Conceptual Schema Design Procedure
3.3 CSDP Step 1: From Examples to Elementary Facts
3.4 CSDP Step 2: Draw Fact Types, and Populate
3.5 CSDP Step 3: Trim Schema; Note Basic Derivations
3.6 Summary
4 Uniqueness Constraints
4.1 CSDP Step 4: Uniqueness Constraints; Arity Check
4.2 Uniqueness Constraints on Unaries and Binaries
4.3 Uniqueness Constraints on Longer Fact Types
4.4 External Uniqueness Constraints
4.5 Key Length Check
4.6 Projections and Joins
4.7 Summary
5 Mandatory Roles
5.1 Introduction to CSDP Step 5
5.2 Mandatory and Optional Roles
5.3 Reference Schemes
5.4 Case Study: A Compact Disc Retailer
5.5 Logical Derivation Check
5.6 Summary
6 Value, Set-Comparison and Subtype Constraints
6.1 CSDP Step 6: Value, Set-Comparison and Subtype constraints
6.2 Basic Set Theory
6.3 Value Constraints and Independent Objects
6.4 Subset, Equality, and Exclusion Constraints
6.5 Subtyping
6.6 Generalization of Object Types
6.7 Summary
7 Other Constraints and Final Checks
7.1 CSDP Step 7: Other Constraints and Final Checks
7.2 Occurrence Frequencies
7.3 Ring Constraints
7.4 Other Constraints and Rules
7.5 Final Checks
7.6 Summary
8 Entity Relationship Modeling
8.1 Overview of ER
8.2 Barker notation
8.3 Information Engineering notation
8.4 IDEF1X
8.5 Mapping from ORM to ER
8.6 Summary
9 Data Modeling in UML
9.1 Introduction
9.2 Object-Orientation
9.3 Attributes
9.4 Associations
9.5 Set-Comparison constraints
9.6 Subtyping
9.7 Other Constraints and Derivation Rules
9.8 Mapping from ORM to UML
9.9 Summary
10 Advanced Modeling Issues
10.1 Join Constraints
10.2 Deontic Rules
10.3 Temporality
10.4 Collection Types
10.5 Nominalization and Objectification
10.6 Open/Closed World Semantics
10.7 Higher-Order Types
10.8 Summary
11 Relational Mapping
11.1 Implementing a Conceptual Schema
11.2 Relational Schemas
11.3 Relational Mapping Procedure
11.4 Advanced Mapping Aspects
11.5 Summary
12 Data Manipulation with Relational Languages
12.1 Relational Algebra
12.2 Relational Database Systems
12.3 SQL: Historical and Structural Overview
12.4 SQL: Identifiers and Data Types
12.5 SQL: Choosing Columns, Rows, and Order
12.6 SQL: Joins
12.7 SQL: In, Between, Like, and Null Operators
12.8 SQL: Union and Simple Subqueries
12.9 SQL: Scalar Operators and Bag Functions
12.10 SQL: Grouping
12.11 SQL: Correlated and Existential Subqueries
12.12 SQL: Recursive Queries
12.13 SQL: Updating Table Populations
12.14 SQL: Other Useful Constructs
12.15 Summary
13 Using Other Database Objects
13.1 SQL: Data Definition
13.2 SQL: User Defined Functions
13.3 SQL: Views and Computed Columns
13.4 SQL: Triggers
13.5 SQL: Stored Procedures
13.6 SQL: Indexes
13.7 Other Objects
13.8 Exploiting 3GLs
13.9 Exploiting XML
13.10 Security and Meta-Data
13.11 Concurrency
13.12 Summary
14 Schema Transformations
14.1 Schema Equivalence and Optimization
14.2 Predicate Specialization and Generalization
14.3 Nesting, Coreferencing, and Flattening
14.4 Other Transformations
14.5 Conceptual Schema Optimization
14.6 Normalization
14.7 Denormalization and Low Level Optimization
14.8 Reengineering
14.9 Data Migration and Query Transformation
14.10 Summary
15 Process and State Modeling
15.1 Introduction
15.2 Processes and Workflow
15.3 Foundations for Process Theory
15.4 State Models versus Process Models
15.5 Modeling Information Dynamics in UML
15.6 Standard Process Patterns
15.7 Business Process Standards Initiatives
15.8 Integration of Process Models and Information Models
15.9 Summary
16 Other Modeling Aspects and Trends
16.1 Introduction
16.2 Data Warehousing and OLAP
16.3 Conceptual Query Languages
16.4 Schema Abstraction Mechanisms
16.5 Further Design Aspects
16.6 Ontologies and the Semantic Web
16.7 Post-Relational Databases
16.8 Metamodeling
16.9 Summary
ORM glossary (ORM 1 and ORM 2)
ER glossary
UML glossary
Bibliography
Index
- No. of pages: 976
- Language: English
- Edition: 2
- Published: March 3, 2008
- Imprint: Morgan Kaufmann
- Hardback ISBN: 9780123735683
- eBook ISBN: 9780080568737
TH
Terry Halpin
Dr. Terry Halpin, is a Principal Scientist at LogicBlox, headquartered in Atlanta, USA, and a Professor at INTI International University, Malaysia. After many years in academia, he worked on data modeling technology at Asymetrix Corporation, InfoModelers Inc., Visio Corporation, and Microsoft Corporation, before returning to academia as Distinguished Professor at Neumont University (Utah, USA), and then once again returning to industry at LogicBlox and also taking a professorship at INTI. His research focuses on conceptual modeling and conceptual query technology. Dr. Halpin is the recipient of the DAMA International Academic Achievement Award and the IFIP Outstanding Service Award. He is a member of IFIP WG 8.1 (Design and Evaluation of Information Systems), is an editor or reviewer for several academic journals and international program committees, has co-chaired several international workshops on modeling, and has presented at dozens of international conferences in both industry and academia. For many years, his research has focused on conceptual modeling and conceptual query technology for information systems, using a business rules approach. His doctoral thesis formalized Object-Role Modeling (ORM/NIAM), and his publications include over 160 technical papers, and six books, including Information Modeling and Relational Databases, Second Edition, Elsevier/Morgan Kaufmann.
Affiliations and expertise
Professor of Computer Science, INTI International University, MalaysiaTM
Tony Morgan
Dr. Tony Morgan is a British computer scientist, data modeling consultant, and Professor in Computer Science at INTI International University, Malaysia. Dr. Morgan obtained his BA in Earth Sciences from The Open University, his BSc in Computer Systems Engineering from Coventry University, where in 1984 he also obtained his MSc in Control Engineering. In 1988 he obtained his PhD in Computer Science from University of Cambridge with a thesis on automated decision-making using qualitative reasoning. Dr. Morgan has done extensive work in industry with companies such as Unisys, EDS, and other corporations across transport, aerospace, government, and financial services, including the UK’s National Computing Centre in Manchester. Dr. Morgan has published several articles on AI and simulation. In 2003 he was appointed Professor of Computer Science and Vice President of Enterprise Informatics at Neumont University, Utah, USA. His research interests focus on business rules and business processes and the rapid development of high-quality information systems. Along with Dr. Halpin, he is the co-author of Information Modeling and Relational Databases, Second Edition, Elsevier/Morgan Kaufmann.
Affiliations and expertise
Professor in Computer Science, INTI International University, MalaysiaRead Information Modeling and Relational Databases on ScienceDirect