Developing High Quality Data Models
1st Edition
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Description
Developing High Quality Data Models provides an introduction to the key principles of data modeling. It explains the purpose of data models in both developing an Enterprise Architecture and in supporting Information Quality; common problems in data model development; and how to develop high quality data models, in particular conceptual, integration, and enterprise data models.
The book is organized into four parts. Part 1 provides an overview of data models and data modeling including the basics of data model notation; types and uses of data models; and the place of data models in enterprise architecture. Part 2 introduces some general principles for data models, including principles for developing ontologically based data models; and applications of the principles for attributes, relationship types, and entity types. Part 3 presents an ontological framework for developing consistent data models. Part 4 provides the full data model that has been in development throughout the book. The model was created using Jotne EPM Technologys EDMVisualExpress data modeling tool.
This book was designed for all types of modelers: from those who understand data modeling basics but are just starting to learn about data modeling in practice, through to experienced data modelers seeking to expand their knowledge and skills and solve some of the more challenging problems of data modeling.
Key Features
- Uses a number of common data model patterns to explain how to develop data models over a wide scope in a way that is consistent and of high quality
- Offers generic data model templates that are reusable in many applications and are fundamental for developing more specific templates
- Develops ideas for creating consistent approaches to high quality data models
Readership
This book is intended for data management professionals with job functions that include data modeler; data architect; database designer; database application developer and application architect.
Table of Contents
Preface
Part 1 Motivations and Notations
Chapter 1 Introduction
1.1 Some Questions about Data Models
1.2 Purpose
1.3 Target Audience
1.4 What Is a Data Model?
1.5 Why Do We Do Data Models?
1.6 Approach to Data Modeling
1.7 Structure of This Book
Chapter 2 Entity Relationship Model Basics
2.1 Oh, Its Boxes and Lines Again
2.2 Graphical or Lexical
2.3 Graphical Notations: Complexity vs. Understandability vs. Capability
2.4 Language and Notation Elements
2.5 Express-G
2.6 Notation for Instances and Classes
2.7 Layout of Data Models
2.8 Reflections
Chapter 3 Some Types and Uses of Data Models
3.1 Different Types of Data Models
3.2 Integration of Data and Data Models
3.3 Concluding Remarks
Chapter 4 Data Models and Enterprise Architecture
4.1 The Business Process Model
4.2 Information Architecture
4.3 Information Operations
4.4 Organization
4.5 Methodologies and Standards
4.6 Management
4.7 Wider Infrastructure
4.8 Enterprise Architecture Mappings
4.9 The Process/Data Balance
Chapter 5 Some Observations on Data Models and Data Modeling
5.1 Limitations of Data Models
5.2 Challenges in Data Modeling
Part 2 General Principles for Data Models
Chapter 6 Some General Principles for Conceptual, Integration, and Enterprise Data Models
6.1 Data Modeling Approach
6.2 General Principles
6.3 Understanding Relationships
6.4 Principles for Data Models
6.5 Naughtiness Index
Chapter 7 Applying the Principles for Attributes
7.1 Looking for Attributes Representing Relationships
7.2 Identifiers
7.3 What Other Attributes Might You Expect?
7.4 Concluding Remarks on Attributes
Chapter 8 General Principles for Relationships
8.1 Example of Inappropriate Cardinalities—Batch and Product Type
8.2 Example of Inappropriate Cardinalities—Packed Products
8.3 An Example of Inappropriate Cardinalities—Ship
8.4 A Good Example of Applying the Principles for Relationships—Transfer and Storage
8.5 Concluding Remarks
Chapter 9 General Principles for Entity Types
9.1 An Example—Combined Entity Types
9.2 An Example—Stock
9.3 Getting Subtypes Wrong
9.4 An Example of Fixed Hierarchies—Stock Classification
9.5 Getting the Right Level of Abstraction
9.6 Impact of Using the Principles
Part 3 An Ontological Framework for Consistent Data Models
Chapter 10 Motivation and Overview for an Ontological Framework
10.1 Motivation
10.2 Ontological Foundation
10.3 A Data Model for the Ontological Foundations
10.4 Closing Remarks
Chapter 11 Spatio-Temporal Extents
11.1 Parts
11.2 Individuals and States
11.3 Inheritance of Properties by Substates
11.4 Space and Time
11.5 Ordinary Physical Objects
11.6 Levels of Reality
11.7 Activities and Events
11.8 Associations
11.9 A Data Model for Individuals
Chapter 12 Classes
12.1 What Is a Set?
12.2 Sets and Four-Dimensionalism
12.3 Some Different Kinds of Set Theory
12.4 A High Level Data Model for Classes
12.5 Properties and Quantities
12.6 Scales and Units
12.7 Kinds
12.8 Concluding Remarks
Chapter 13 Intentionally Constructed Objects
13.1 Introduction
13.2 Functional Objects
13.3 Socially Constructed Objects
13.4 Ownership
13.5 Agreements
13.6 Contracts
13.7 Organizations
13.8 Product
13.9 Representation
13.10 Concluding Remarks
Chapter 14 Systems and System Components
14.1 What Are Systems and System Components?
14.2 The Nature of System Components
14.3 Another Example: A Football Match
14.4 Similarities, Differences, and Relationships to Other Things
14.5 Do I Need a Separate Set of Classes for System Components?
14.6 Extending the Framework for System and System Component
14.7 Concluding Remarks
Chapter 15 Requirements Specification
15.1 A Process for Procurement
15.2 Requirements Specification
Chapter 16 Concluding Remarks
Part 4 The HQDM Framework Schema
Chapter 17 HQDM_Framework
17.1 Thing and Abstract Object
17.2 Class and Class of Class
17.3 Relationship and Class of Relationship
17.4 Spatio-Temporal Extent and Class of Spatio-Temporal Extent
17.5 Event, Class of Event, and Point in Time
17.6 State and Individual
17.7 Physical Object
17.8 Ordinary Physical Object
17.9 Kind of Individual and Subtypes
17.10 Kind of System and System Component
17.11 Period of Time and Possible Worlds
17.12 Physical Properties and Physical Quantities
17.13 Association
17.14 Activity
17.15 Participant
17.16 Role, Class of Activity, and Class of Association
17.17 System
17.18 System Component
17.19 Installed Object
17.20 Biological Object
17.21 Ordinary Biological Object
17.22 Biological System
17.23 Person
17.24 Biological System Component
17.25 Intentionally Constructed Object
17.26 Functional Object
17.27 Ordinary Functional Object
17.28 Functional System
17.29 Socially Constructed Object
17.30 Party
17.31 Organization and Language Community
17.32 Employment
17.33 Organization Component and Position
17.34 Money
17.35 Ownership
17.36 Transfer of Ownership
17.37 Socially Constructed Activity
17.38 Class of Socially Constructed Activity
17.39 Agreement
17.40 Contract
17.41 Offer and Acceptance of Offer
17.42 Sale of Goods
17.43 Sales Product, Product Brand, and Sales Product Version
17.44 Offering
17.45 Sign and Pattern
17.46 Requirement and Requirement Specification
Appendix: A Mapping between the HQDM Schema and ISO 15926-2
Index
Details
- No. of pages:
- 408
- Language:
- English
- Copyright:
- © Morgan Kaufmann 2011
- Published:
- 30th December 2010
- Imprint:
- Morgan Kaufmann
- Paperback ISBN:
- 9780123751065
- eBook ISBN:
- 9780123751072
About the Author
Matthew West
Matthew West spent over 20 years as a leading data modeler for Shell where he was a key technical contributor to data modeling and data management standards and their application. Matthew was responsible for Shell's Downstream Data Model. He currently serves as the Director of Information Junction, a data architecture and analysis consultancy in the UK. He is also a key contributor to ISO 15926 (Lifecycle integration of process data) and ISO 8000 (Data and Information Quality). Matthew is a Visiting Professor at the University of Leeds
Affiliations and Expertise
Director of Information Junction, UK
Reviews
"This guide to developing high quality data models provides practical instruction in understanding the core principle of data modeling and creating accurate models from complex databases. The work is divided into four sections covering the basics of data model types and uses, general principles for data model components and an ontological framework for consistent data models. A final section presents a complete, standards compliant data model created with the Jotne EPM Technology EDMVisusalExpress data modeling tool. Numerous illustrations, charts and sample programming code are included throughout the work and access to additional online content, including the sample data model, is provided. West is an experienced data modeler working in the energy field."--Book News, Reference & Research
"Overall, the book is a helpful guide for those who wish to go deep into the art of developing high quality data models. Readers will appreciate: how West connects data models with EA and business processes; the ontological approach, which offers a framework for formal, generic, and consistent models; the efficient use of diagrams for explaining the notions; and the philosophical concepts discussed throughout the text. The book is highly technical. Although it does not directly address people from academia, it will be very useful for related courses, especially those that deal with IT and business processes. Finally, the book highlights the importance of quality in data modeling for decision making."--Computing reviews.com
Ratings and Reviews
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