Temporal Data & the Relational Model (The Morgan Kaufmann Series in Data Management Systems) [Paperback]

C.J. Date (Author), Hugh Darwen (Author), Nikos Lorentzos (Author)

Book Description

ISBN-10: 1558608559 | ISBN-13: 978-1558608559 | Publication Date: December 3, 2002 | Edition: 1

Temporal database systems are systems that provide special support for storing, querying, and updating historical and/or future data. Current DBMSs provide essentially no temporal features at all, but this situation is likely to change soon for a variety of reasons; in fact, temporal databases are virtually certain to become important sooner rather than later, in the commercial world as well as in academia. This book provides an in-depth description of the foundations and principles on which those temporal DBMSs will be built. These foundations and principles are firmly rooted in the relational model of data; thus, they represent an evolutionary step, not a revolutionary one, and they will stand the test of time.

This book is arranged in three parts and a set of appendixes:

* Preliminaries: Provides a detailed review of the relational model, and an overview of the Tutorial D language.
* Laying the Foundations: Explains basic temporal data problems and introduces fundamental constructs and operators for addressing those problems.
* Building on the Foundations: Applies the material of the previous part to issues of temporal database design, temporal constraints, temporal query and update, and much more.
* Appendixes: Include annotated references and bibliography, implementation considerations, and other topics.

Key features:

* Describes a truly relational approach to the temporal data problem.
* Addresses implementation as well as model issues.
* Covers recent research on new database design techniques, a new normal form, new relational operators, new update operators, a new approach to the problem of "granularity," support for "cyclic point types," and other matters.
* Includes review questions and exercises in every chapter.
* Suitable for both reference and tutorial purposes.

Editorial Reviews

From the Back Cover

Temporal database systems are systems that provide special support for storing, querying, and updating historical and/or future data. Current DBMSs provide essentially no temporal features at all, but this situation is likely to change soon for a variety of reasons; in fact, temporal databases are virtually certain to become important sooner rather than later, in the commercial world as well as in academia. This book provides an in-depth description of the foundations and principles on which those temporal DBMSs will be built. These foundations and principles are firmly rooted in the relational model of data; thus, they represent an evolutionary step, not a revolutionary one, and they will stand the test of time.

This book is arranged in three parts and a set of appendixes:

• Preliminaries: Provides a detailed review of the relational model, and an overview of the Tutorial D language.
  
• Laying the Foundations: Explains basic temporal data problems and introduces fundamental constructs and operators for addressing those problems.
  
• Building on the Foundations: Applies the material of the previous part to issues of temporal database design, temporal constraints, temporal query and update, and much more.
  
• Appendixes: Include annotated references and bibliography, implementation considerations, and other topics.

Key features:

• Describes a truly relational approach to the temporal data problem.
  
• Addresses implementation as well as model issues.
  
• Covers recent research on new database design techniques, a new normal form, new relational operators, new update operators, a new approach to the problem of "granularity," support for "cyclic point types," and other matters.
  
• Includes review questions and exercises in every chapter. Solutions are available at www.mkp.com.
  
• Suitable for both reference and tutorial purposes.

About the Author

By C.J. Date, Nikos Lorentzos and Hugh Darwen

Product Details

• Paperback: 422 pages
• Publisher: Morgan Kaufmann; 1 edition (December 3, 2002)
• Language: English
• ISBN-10: 1558608559
• ISBN-13: 978-1558608559
• Product Dimensions: 9.1 x 7.3 x 0.9 inches
• Shipping Weight: 1.7 pounds (View shipping rates and policies)
• Average Customer Review: 4.4 out of 5 stars  See all reviews (5 customer reviews)
• Amazon Best Sellers Rank: #632,504 in Books (See Top 100 in Books)

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Customer Reviews

Most Helpful Customer Reviews

72 of 74 people found the following review helpful:

5.0 out of 5 stars Impressive, But Daunting, December 14, 2002

By 

David Lawrence (Cambridge, MA) - See all my reviews
(REAL NAME)   

This review is from: Temporal Data & the Relational Model (The Morgan Kaufmann Series in Data Management Systems) (Paperback)

This book presents perhaps the first rigorous analysis of the issues surrounding the use of temporal data in a relational database. Temporal data may be thought of as information contained in relations (i.e. tables) which changes over time. This situation most often arises in data warehouse environments, but the authors rightly point out that current data (e.g. in an Operational Data Store) must be integrally related to the history of that data over time.

This book is not for the faint-hearted. Its approach is quite rigorous and abstract. In order to comprehend this book in any meaningful fashion, the reader will have to develop an understanding of predicate calculus, which is a specialized version of set theory and its logic. Previous exposure to "Foundation for Object/Relational Databases: The Third Manifesto," by Date and Darwen, is highly recommended. While their approach is necessary, it does entail endless dry proofs of the prerequisite material needed to develop a general theory of temporal data. The authors leave few issues not covered in an effort to present a fully rigorous analysis of the issues. The book practically begs for a companion book to present a simplified summary of their findings and to contrast them with current data warehouse practices.

The book begins with a review of relational concepts and an introduction to Tutorial D, which was first presented in "The Third Manifesto." The authors then develop a theory of time in the database, which is based on earlier work by Lorentzos. Their approach is to create a new data type for timestamped data and, more importantly, for intervals of time. After developing a relational model for these temporal constructs, they propose a generic design for current, historical and current and historical databases using the Supplier-Parts Database which readers will likely have been exposed to in previous writings by Date. They develop methods to implement integrity constraints, queries and updates, and make a valid comparison between stated times, which are beliefs about the data, and logged times, which are facts the database records about these beliefs. Since our beliefs about time can change, this is an important distinction.

The overall approach is to develop a model of data which is highly related to an audit trail, which should be viewed distinctly from the concept of a database transaction log. Unfortunately, in order to implement the model, an interval timestamp is required for every attribute, and historical data must be presented in the Sixth Normal Form, which they introduce as a decomposition of each historical record into a relation for each data attribute, with its associated timestamp.

While their approach is entirely correct, realization of their ideas would be a prohibitive task in current databases. A database that provided an automated construction of current and historical values would be necessary to implement their model in a consistent and economical fashion. Their solution is in many ways radically different than the typical "Facts and Dimensions" approach of star-schema data warehouses which are the most popular current tool for the analysis of historical data. The utility of the dimensional "slice and dice" approach to data analysis is beyond doubt, and the authors would need to provide some mechanism to allow for this type of analysis to be performed under their alternative approach in order for a commercial database vendor to consider supporting their propositions.

Still, there is much original insight to be gleaned from the author's analyses which will reward anyone who has the talent and perseverance to thoroughly read this book. I especially like the way in which the book provides an integrated means of analysis for current and historical data. Far too many other authors in the data warehouse literature have ignored at their own peril the undeniable link between transactional and analytic data. I can only hope that database vendors are sufficiently inspired by this book to implement their eminently reasonable and logically correct answers to the questions of temporal data.

18 of 22 people found the following review helpful:

5.0 out of 5 stars Some solid ground at last, August 15, 2003

By 

Stuart Roberts (Leeds, UK) - See all my reviews

This review is from: Temporal Data & the Relational Model (The Morgan Kaufmann Series in Data Management Systems) (Paperback)

My thanks go to the authors for this book. Lat year I introduced material on temporal databases to my undergraduate students, realising the importance of this topic. However I did not feel comfortable with the books that deal with temporal database or confident that the prevailing approach was sound. Here the authors make crystal clear every decision as to how to model things. The relational model once again provides a foundation which leads to confidence even though the full temporal datbase picture is not yet in sight. As I read the book I found I got engaged in the subject and started asking my own questions (which were often answered later on) - a sign of a good book!. Now I'm using it in earnest to revise my lecture notes for next session, and am appreciating the structure of the book: the order in which topics are introduced and the use of examples. This is not just (maybe not primarily) a student text book, but I would recommend reading it to anyone teaching temporal database.

2 of 2 people found the following review helpful:

5.0 out of 5 stars Long Overdue Clarity on a Complex Subject, December 30, 2007

By 

SeánMacGC "SeánMacGC" (Ireland) - See all my reviews

This review is from: Temporal Data & the Relational Model (The Morgan Kaufmann Series in Data Management Systems) (Paperback)

There can be no denying, I believe, that insofar as current major Database Management Systems (DBMS) are concerned, temporal data represents a significant problem: it is simply not possible to declaratively constrain the integrity of temporal data in SQL databases (or non-temporal data, even). I am not alone I am sure in having had to deal with duplicate, triplicate, quadruplicate, etc., records covering, or abutting, or overlapping on the same temporal periods. Not to mention the hoops that must be jumped through to reliably manipulate those same data.

Date, Darwen, and Lorentzos have produced a formidable work here on applying some badly needed rigid logic to the whole sphere of temporal data within databases. And that rigid logic is afforded by the Relational Model. They consider three variants on the temporal data theme as vehicles for explanation and demonstration: 1. Semitemporal with current data only, 2. Temporal with current and historical data held within the same relvars (tables), 3. Temporal with current and historical data split into separate relvars.

Temporal data is a complex area, so this book has, inevitably, had to get 'down and dirty' with the detail, but the authors are clear and comprehensive throughout. A thorough familiarity with the Relational Model will help, as will any previous experience of their Relational language `Tutorial D', though they go though both in the first two introductory chapters.

We would indeed be much better off were the DBMS vendors to take serious note of the powerful logical arguments laid forth in this volume, and far from interpreting their reflections (criticisms) on NULLs, etc., as 'political', I would see them only as further reaffirmations of the principles that have led them to invest so much endeavour and thought into the problems and very real deficiencies of data modelling and integrity, specifically in regard to the Relational Model. And for that we should indeed be thankful.