Applied Contaminant Transport Modeling Review

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(More customer reviews)This book provided an excellent explanation of the modeling of solutes and groundwater that conveyed a very good understanding of the challenges and methods used without resorting to the use of mathematical sophistication that actual ground water modelers no doubt possess.
In other words, I think that this book would benefit both those that are hydrologists and geologists as well as those that have had some training in environemental site assessment and remediation but have not been exposed to the actual number crunching that is essential for doing actual simulations.

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The challenges facing groundwater scientists and engineers today demand expertise in a wide variety of disciplines–geology, hydraulics, geochemistry, geophysics, and biology. As the number of the subdisciplines has increased and as each has become more complex and quantitative, the problem of integrating their concepts and contributions into a coherent overall interpretation has become progressively more difficult. To an increasing degree transport simulation has emerged as an answer to this problem, and the transport model has become a vehicle for integrating the vast amount of field data from a variety of sources and for understanding the relationship of various physical, chemical, and biological processes.
Applied Contaminant Transport Modeling is the first resource designed to provide coverage of the discipline's basic principles, including the theories behind solute transport in groundwater, common numerical techniques for solving transport equations, and step-by-step guidance on the development and use of field-scale modeling. The Second Edition incorporates recent advances in contaminant transport theory and simulation techniques, adding the following to the original text:
-An expanded discussion of the role of aquifer heterogeneity in controlling solute transport-A new section on the dual-domain mass transfer approach as an alternative to the classical advection-dispersion model-Additional chemical processes and reactions in the discussion of reactive transport-A discussion of the TVD (total-variation-diminishing) approach to transport solution-An entirely new Part III containing two chapters on simulation of flow and transport under variable water density and under variable saturation, respectively, and a third chapter on the use of the simulation-optimization approach in remediation system design
Applied Contaminant Transport Modeling, Second Edition remains the premier reference for practicing hydrogeologists, environmental scientists, engineers, and graduate students in the field. In 1998, in recognition of their work on the first edition, the authors were honored with the John Hem Excellence in Science and Engineering Award of the National Ground Water Association

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Mathematical Modeling, Third Edition Review

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(More customer reviews)In this book you'll find, fully explained, subjects that are only mentioned briefly in other texts on modeling. I liked the chapter (chapter five) on Eigenvalue Methods for the analysis of dynamic models. I wished I had it four years ago when I was taking a course on modeling at the University of Washington. It really shows you how to do it. The same can be said about chapters 2 and 3 on optimization and chapters 7 and 8 on probability models (I liked specially the one on Markov Chains). I'm using it for teaching those techniques. The pseuodocode it includes is particularly helpful when you take the methods presented in the book to the computer. However, I would not recomend it to be used on its own as the only text in a course. It is a nice complement to texts like Gurney and Nisbet's Ecological Dynamics that presents many particular models in detail, while Meerschaert makes enphasis on general techniques. It's also a step up the ladder from "abc-of-modeling-techniques" texts like Vandermeer's Elementary Mathemathical Ecology. With 20/20 hindsight, if I had to learn modeling from the begining (or, if I had to teach it as I'm doing now) I would choose these titles as a step-by-step system, coupled with some Math packages like MathCad or Matlab.

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Biomedical Signal Processing and Signal Modeling Review

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(More customer reviews)Good book for looking at the mathematics behind biomedical signal processing. If your going to use Matlab in conjunction with your study of this book, I used "Biosignal and Biomedical Image Processing: Matlab-Based Applications," by John L. Semmlow.

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Introducing Multilevel Modeling (Introducing Statistical Methods series) Review

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(More customer reviews)When analysing data, the relationships between people that belong in the same classroom, live in the same street or suburb, are part of the same family or therapy group,etc., are often ignored. Multilevel or hierarchical linear modelling is a statistical technique for taking into account such dependencies, arranged in hierarchies (e.g., correlations between students within classrooms, correlations between classrooms within schools, correlations between schools within school districts). In other words, multilevel modeling techniques attempt to model the hierarchical relationships that are found in the real world. In the last 10 years or so there has been a growing number of books and software packages concerned with multilevel analyses. Introducing Multilevel Modeling is shorter and slightly less 'mathematical' than most and gives quite a good introduction to the subject. The book makes reference to the British MLn (MLWiN) computer program in its examples, whereas an introductory text arguably should have used the HLM program, for which a cutdown student version is available free. Taking group dependencies into account is extremely important, but unfortunately many researchers will be discouraged by the dry and heavy-going feel of these texts, which is so often the case with anything involving statistical theory. A highly approachable and readable book remains to be written, but Introducing Multilevel Modeling is probably the best of the current crop.

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This is the first accessible and practical guide to using multilevel models in social research.



Multilevel approaches are becoming increasingly important in social, behavioural, and educational research and it is clear from recent developments that such models are seen as being more realistic, and potentially more revealing, than ordinary regression models.



While other books describe these multilevel models in considerable detail none focuses on the practical issues and potential problems of doing multilevel analyses that are covered in Introducing Multilevel Modeling.



The authors' approach is user-oriented and the formal mathematics and statistics are kept to a minimum. Other key fe

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Structural Equation Modeling: A Second Course (Quantitative Methods in Education and the Behavioral Science) Review

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(More customer reviews)This book fills an important niche, a sweet spot in between basic SEM texts such as Rex Kline's helpful beginner's book and more complex, advanced treatments of SEM such as Ken Bollen's classic 1989 Wiley text. Methodologists might argue that the latter text is intermediate rather than advanced, but practitioners and applied users of SEM who are not in the business of creating new methods but instead want to use SEM in a rigorous, productive way on applied analysis problems will find this text to be just the ticket to getting things done using SEM and tackling typical problems such as how to handle missing data and how to calculate power for goodness-of-fit tests and parameter estimates.
The editors have done a terrific job in working with the chapter authors to make all chapters accessible with helpful examples and consistent notation and terminology. This book, along with Loehlin's Latent Variable Models, is one I find myself pulling off my bookcase repeatedly to solve applied problems or to learn more about a particular SEM issue (modeling options for complex survey data, mixture modeling) quickly, yet comprehensively. Highly recommended.

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A volume in Quantitative Methods in Education and the Behavioral Sciences:Issues, Research, and Teaching
(sponsored by the American Educational Research Association's Special Interest Group:Educational Statisticians)
Series EditorRonald C. Serlin, University of Wisconsin-Madison
This volume is intended to serve as a didactically-oriented resource covering a broad range of advanced topics often not discussedin introductory courses on structural equation modeling (SEM). Such topics are important in furthering the understandingof foundations and assumptions underlying SEM as well as in exploring SEM as a potential tool to address new types ofresearch questions that might not have arisen during a first course. Chapters focus on the clear explanation and application oftopics, rather than on analytical derivations, and contain syntax and partial output files from popular SEM software.
CONTENTS: Introduction to Series, Ronald C. Serlin. Preface, Richard G. Lomax. Dedication. Acknowledgements. Introduction,Gregory R. Hancock & Ralph O. Mueller. Part I: Foundations. The Problem of Equivalent Structural Models, Scott L.Hershberger. Formative Measurement and Feedback Loops, Rex B. Kline. Power Analysis in Covariance Structure Modeling,Gregory R. Hancock. Part II: Extensions. Evaluating Between-Group Differences in Latent Variable Means, Marilyn S.Thompson & Samuel B. Green. Using Latent Growth Models to Evaluate Longitudinal Change, Gregory R. Hancock & FrankR. Lawrence. Mean and Covariance Structure Mixture Models, Phill Gagné. Structural Equation Models of Latent Interactionand Quadratic Effects, Herbert W. Marsh, Zhonglin Wen, & Kit-Tai Hau. Part III: Assumptions. Nonnormal and CategoricalData in Structural Equation Modeling, Sara J. Finney & Christine DiStefano. Analyzing Structural Equation Models withMissing Data, Craig K. Enders. Using Multilevel Structural Equation Modeling Techniques with Complex Sample Data,Laura M. Stapleton. The Use of Monte Carlo Studies in Structural Equation Modeling Research, Deborah L. Bandalos. Aboutthe Authors.

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The Data Modeling Handbook : A Best-Practice Approach to Building Quality Data Models Review

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(More customer reviews)I have many books on data modeling but this one is probably the most understandable. The examples are well-formed and many diagrams are provided along with written explanations. They do an excellent job of going through 5th normal form and show how to resolve many different issues such as special cases in generalization hierarchies. I have found this book very useful in practice and it has served me well.

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Mathematics for Dynamic Modeling, Second Edition Review

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(More customer reviews)This is not a new cover on an older book. Having enjoyed Beltrami's first book I was glad to see a second. The new continues the subject of modeling not math. Well written, the author's book ties the conceptual difficulites of the subjects with the necessary math to get the point accross and guide the reader to new frontiers of insight again in the sense of the physical model not the math. This is a very important point! One does not lose sight of the over-all objective as with some math intensive proof types. The beauty of the work is getting the necessary across with the least. One disappointment though. The book was to short. I hope the author continues another work. Perhaps some more indepth of previous covered material. All examples and problems are easily solved in Mathcad, which already has the depth but sometimes not the explanation.

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Applied Management Science: Modeling, Spreadsheet Analysis, and Communication for Decision Making, 2nd Edition Review

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(More customer reviews)I was a student at Cal State Fullerton, where these professors teach. This is the worst textbook I have ever read. The text is poorly written. The book doesn't read well and has many typos. I would have expected more from the Management Science Department Chair.

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Modeling Infectious Diseases in Humans and Animals Review

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(More customer reviews)this is an excellent and elementary introduction for beginners, especially undergraduates. the author has introduced a large number of modellings in this field as clearly as possible. nevertheless, the mathematical analysis, the ordinary differential equation and even nonlinear dynamics should be mastered before reading this book.

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For epidemiologists, evolutionary biologists, and health-care professionals, real-time and predictive modeling of infectious disease is of growing importance. This book provides a timely and comprehensive introduction to the modeling of infectious diseases in humans and animals, focusing on recent developments as well as more traditional approaches.

Matt Keeling and Pejman Rohani move from modeling with simple differential equations to more recent, complex models, where spatial structure, seasonal "forcing," or stochasticity influence the dynamics, and where computer simulation needs to be used to generate theory. In each of the eight chapters, they deal with a specific modeling approach or set of techniques designed to capture a particular biological factor. They illustrate the methodology used with examples from recent research literature on human and infectious disease modeling, showing how such techniques can be used in practice. Diseases considered include BSE, foot-and-mouth, HIV, measles, rubella, smallpox, and West Nile virus, among others. Particular attention is given throughout the book to the development of practical models, useful both as predictive tools and as a means to understand fundamental epidemiological processes. To emphasize this approach, the last chapter is dedicated to modeling and understanding the control of diseases through vaccination, quarantine, or culling.

Comprehensive, practical introduction to infectious disease modeling
Builds from simple to complex predictive models
Models and methodology fully supported by examples drawn from research literature
Practical models aid students' understanding of fundamental epidemiological processes
For many of the models presented, the authors provide accompanying programs written in Java, C, Fortran, and MATLAB
In-depth treatment of role of modeling in understanding disease control

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Texturing and Modeling, Third Edition: A Procedural Approach (The Morgan Kaufmann Series in Computer Graphics) Review

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(More customer reviews)This is an update of a classic book on procedural texturing and modeling by the main founders of the field. The book presents lengthy discussions of classical procedural texturing using various noise functions of the sort originated by Ken Perlin (one of the authors). It discusses newer texturing techniques such as cellular texturing, which can be used, for example, to create convincing stone patterns. Other chapters focus on animating solid textures (e.g. marble forming, volumetric gasses, etc.), fractal terrain generation, and tips for utilizing existing graphics APIs and hardware for realtime procedural texturing. This is only a sampling of the topics covered.
Code samples in C and RenderMan are given throughout, although most algorithms are given in only one of those languages. This can be a bit of a problem, as many readers will probably not have access to a RenderMan implementation. Nevertheless, it is not too difficult to translate the RenderMan code into C code in many instances.
The biggest drawback to this book is its lack of rigorous technical coverage. The decision to omit many mathematical details was a conscious choice on the part of the authors. Instead the book is mostly prose discussion of the techniques and the coarse descriptions of the underlying concepts. Although the prose is mostly clear, many times I felt myself in need of more specific, technical details. Fortunately, the book's authors are the primary researchers in this field and most of the ideas in the book have been published in academic journals. It was very easy to supplement the book with these primary sources.
Overall I found this to be a very interesting and useful book, with many algorithms essentially ready-to-run right out of the book. It would get five stars, except for the lack of technical and mathematical details mentioned above. Every serious worker in graphics needs to have this book on their shelf. I use mine often.

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The third edition of this classic tutorial and reference on procedural texturing and modeling is thoroughly updated to meet the needs of today's 3D graphics professionals and students. New for this edition are chapters devoted to real-time issues, cellular texturing, geometric instancing, hardware acceleration, futuristic environments, and virtual universes. In addition, the familiar authoritative chapters on which readers have come to rely contain all-new material covering L-systems, particle systems, scene graphs, spot geometry, bump mapping, cloud modeling, and noise improvements. There are many new spectacular color images to enjoy, especially in this edition's full-color format.As in the previous editions, the authors, who are the creators of the methods they discuss, provide extensive, practical explanations of widely accepted techniques as well as insights into designing new ones. New to the third edition are chapters by two well-known contributors: Bill Mark of NVIDIA and John Hart of the University of Illinois at Urbana-Champaign on state-of-the-art topics not covered in former editions.An accompanying Web site (www.texturingandmodeling.com) contains all of the book's sample code in C code segments (all updated to the ANSI C Standard) or in RenderMan shading language, plus files of many magnificent full-color illustrations.No other book on the market contains the breadth of theoretical and practical information necessary for applying procedural methods. More than ever, Texturing & Modeling remains the chosen resource for professionals and advanced students in computer graphics and animation.*New chapters on: procedural real-time shading by Bill Mark, procedural geometric instancing and real-time solid texturing by John Hart, hardware acceleration strategies by David Ebert, cellular texturing by Steven Worley, and procedural planets and virtual universes by Ken Musgrave.*New material on Perlin Noise by Ken Perlin.*Printed in full color throughout.*Companion Web site contains revised sample code and dozens of images.

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Credit Risk Modeling: Theory and Applications (Princeton Series in Finance) Review

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(More customer reviews)The author briefly touched many models without quite understanding them himself (or checking their validity). Most of the text were collected (and rewritten) from reading the abstract or conclusion of the original papers. There is not enough insight or new info. It is absolutely not a book for someone who wants to learn because it is like a undergraduate's study report. If a book reviews many models, it should provide some insights, pros and cons of them, and at least some framework for other researchers to follow. It loses value if it merely rephrases some obvious and straghtforward assumptions of the original models.
I admire the author and the editor (Duffie) as researchers. However, the author is not ready yet to write a book of this kind and the editor has been a super star in finance, hence should not lower himself to this level for the sake of publication. This book does not provide useful info at all. Not good for a researcher or a practitioner (at all). Why not read the original papers' abstracts? That would be more informative.

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Credit risk is today one of the most intensely studied topics in quantitative finance. This book provides an introduction and overview for readers who seek an up-to-date reference to the central problems of the field and to the tools currently used to analyze them. The book is aimed at researchers and students in finance, at quantitative analysts in banks and other financial institutions, and at regulators interested in the modeling aspects of credit risk.

David Lando considers the two broad approaches to credit risk analysis: that based on classical option pricing models on the one hand, and on a direct modeling of the default probability of issuers on the other. He offers insights that can be drawn from each approach and demonstrates that the distinction between the two approaches is not at all clear-cut. The book strikes a fruitful balance between quickly presenting the basic ideas of the models and offering enough detail so readers can derive and implement the models themselves. The discussion of the models and their limitations and five technical appendixes help readers expand and generalize the models themselves or to understand existing generalizations. The book emphasizes models for pricing as well as statistical techniques for estimating their parameters. Applications include rating-based modeling, modeling of dependent defaults, swap- and corporate-yield curve dynamics, credit default swaps, and collateralized debt obligations.

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Hydrodynamics and Transport for Water Quality Modeling Review

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(More customer reviews)This book provides a good fundamentals on learning the movement of water and chemicals in water. The different conepts in applying models for a specific study can be judged using this book.

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Hydrodynamics and Transport for Water Quality Modeling presents a complete overview of current methods used to describe or predict transport in aquatic systems, with special emphasis on water quality modeling. The book features detailed descriptions of each method, supported by sample applications and case studies drawn from the authors' years of experience in the field. Each chapter examines a variety of modeling approaches, from simple to complex. This unique text/reference offers a wealth of information previously unavailable from a single source.The book begins with an overview of basic principles, and an introduction to the measurement and analysis of flow. The following section focuses on rivers and streams, including model complexity and data requirements, methods for estimating mixing, hydrologic routing methods, and unsteady flow modeling. The third section considers lakes and reservoirs, and discusses stratification and temperature modeling, mixing methods, reservoir routing and water balances, and dynamic modeling using one-, two-, and three-dimensional models. The book concludes with a section on estuaries, containing topics such as origins and classification, tides, mixing methods, tidally averaged estuary models, and dynamic modeling. Over 250 figures support the text.This is a valuable guide for students and practicing modelers who do not have extensive backgrounds in fluid dynamics.

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Environmental Systems and Processes: Principles, Modeling, and Design Review

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(More customer reviews)I am an envoronmental engineering student, and my instructor for a course used this book. I thought it was cumbersome to use, I came from a civil engineering department, as much of it was referencing chemical engineering material without sufficient review and background. I also thought that it made so much reference to PDES, weber's other text, that it should just be included as part of that book. I wouldnt recommend this to another sudent.

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Software Modeling and Design: UML, Use Cases, Patterns, and Software Architectures Review

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(More customer reviews)If you want to learn to use UML as a communication tool on your software development projects, this is the book too own. It contains a ton of examples and covers every aspect of the UML you will need to know to successfully use it on your projects.
The book starts out with an introduction to software architecture and object oriented analysis and design with UML.
There is then a short chapter on UML notation, a chapter on software development processes, and one on software design and architectural concepts. The last chapter in part one introduces COMET (Collaborative Object Modeling and Architectural Design Method), which is the author's software modeling and design method.
To me COMET is not really that much different than the Unified Process, which is a great process. COMET just breaks out the testing activities a little differently. COMET is a very usable process and if used correctly should lead to successful software development projects.
Part two of the book is all about modeling. There is a chapter on Use Case Modeling, Static Modeling, Object and Class Structuring, Dynamic Interaction Modeling, Finite State Machines, and State-Dependent Dynamic Interaction Modeling.
By the time you are done with part two of this book you will know all you need to know to produce high quality diagrams that can be used between the different stakeholders on your projects as very effective communication tools.
Part three of the book covers software architecture. There is a chapter on the Overview of Software Architecture, Software Subsystem Architectural Design, Designing Object-Oriented Software Architectures, Designing Client/Server Software Architectures, Designing Service-Oriented Architectures, Designing Component-Based Software Architectures, Designing Concurrent and Real-Time Software Architectures, Designing Software Product Line Architectures, and a chapter on Software Quality Attributes.
If the chapter on Software Product Lines interests you, I would highly recommend buying the author's book tilted Designing Software Product Lines with UML: From Use Cases to Pattern-Based Software Architectures.
I really the like the way part two introduces the different perspectives you need to have when considering the type of architecture you are building. The way the author accomplishes this is unique to this book. I have not seen it broken down this way before, and it really provides some great insight.
Part three contains several case studies. Each one provides a detailed design of the system being discussed. These are great for seeing how well the design techniques in this book work. You get a complete understanding of each of the systems in the case studies by the time you are done reading the chapter.
This book is really well written and organized. You can read it from front to back or use it as a reference. Each chapter ends with exercise questions. I usually just ignore these, but since the author has decided to include the answers I enjoyed trying to answer them.
The book has an appendix which contains a nice catalog of software architectural patterns. It is a summary of architectural structure patterns, communication patterns, and transaction patterns. It contains a summary of the pattern and the location it is used in the book.
All in all this is a very high quality book packed with very valuable information any architect at an level of experience will benefit from. Hi highly recommend this book!!!!

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Modeling Derivatives Applications in Matlab, C++, and Excel Review

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(More customer reviews)I highlight two points:
1. The inclusion of Matlab and Excel code in almost all topics of the book.
2. All the content is new and more advanced, there is no recovered topics of his previous book.


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Prebuilt Code for Modeling and Pricing Today's Complex DerivativesJustin London shows how to implement pricing algorithms for a wide variety of complex derivatives, including rapidly emerging instruments covered in no other book. Utilizing actual Bloomberg data, London covers credit derivatives, CDOs, mortgage-backed securities, asset-backed securities, fixed-income securities, and today's increasingly important weather, power, and energy derivatives.His robust models are designed for both ease of use and ease of adaptation, and may be downloaded by the book's purchasers from a secured Web site.Modeling Derivatives Applications in Matlab, C++, and Excel will be indispensable to sell-side professionals who model derivatives; buy-side professionals who must understand the derivatives offered to them; experienced quants; developers at Wall Street firms; and any financial engineering practitioner or student entering the derivatives field for the first time.Presents broader coverage and more models than any competitive book Covers everything from swaps to interest rate models, mortgage- and asset-backed securities to the HJM model Includes code for all three leading derivatives development platforms The only book to present models for Matlab, C++, and Excel Addresses the fastest-growing areas of derivatives development Includes models for weather, power, and energy derivatives, CDOs, and more Contains extensive real-world examples. Theentire book utilizesMatlab, C++, and Excel. Users need Matlab installed, Visual C++, and Excel.In addition, some examples using Matlab toolkits are used: Chapter 1makes use of the Fixed-Income Toolkit. Appendix A makes use of the Financial Derivatives Toolkit and Matlab Excel Link.These toolkits do not come with the book, but can be obtained from Mathworks.Downloadable models available ONLY to purchasers of this book.Purchasers receive a unique access code enabling secure access to downloadable, prebuilt code and templates for Matlab, C++, and Excel. Preface xv Acknowledgments xix About the Author xxiChapter 1Swaps and Fixed Income Instruments 1 Chapter2 Copula Functions 67Chapter3 Mortgage-Backed Securities 91Chapter4 Collateralized Debt Obligations 163Chapter5 Credit Derivatives 223Chapter6Weather Derivatives 299Chapter7 Energy and Power Derivatives 333Chapter8 Pricing Power Derivatives: Theory and Matlab Implementation 407Chapter9 Commercial Real Estate Asset-Backed Securities 447Appendix AInterest Rate Tree Modeling in Matlab 473Appendix BChapter 7 Code 503 References 543 Index 555

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Introduction to Credit Risk Modeling, Second Edition (Chapman & Hall/CRC Financial Mathematics Series) Review

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(More customer reviews)The book proceeds mostly as theorem, proof, theorem, proof, but the proofs are incomplete. Many of the proofs simply cite a reference, I do not consider that a proof at all.
Nearly every paragraph cites multiple references, and claims the topic is outside the scope of the book and the reader should refer to some other book. It seems that most everything the book covers is in some way or another "out of the scope" of the book.
The flow is incoherent. Chapters 1 and 2 frequently cite figures and sections in chapter 4 and beyond.

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Contains Nearly 100 Pages of New MaterialThe recent financial crisis has shown that credit risk in particular and finance in general remain important fields for the application of mathematical concepts to real-life situations. While continuing to focus on common mathematical approaches to model credit portfolios, Introduction to Credit Risk Modeling, Second Edition presents updates on model developments that have occurred since the publication of the best-selling first edition.New to the Second EditionAn expanded section on techniques for the generation of loss distributionsIntroductory sections on new topics, such as spectral risk measures, an axiomatic approach to capital allocation, and nonhomogeneous Markov chainsUpdated sections on the probability of default, exposure-at-default, loss-given-default, and regulatory capital A new section on multi-period modelsRecent developments in structured creditThe financial crisis illustrated the importance of effectively communicating model outcomes and ensuring that the variation in results is clearly understood by decision makers. The crisis also showed that more modeling and more analysis are superior to only one model. This accessible, self-contained book recommends using a variety of models to shed light on different aspects of the true nature of a credit risk problem, thereby allowing the problem to be viewed from different angles.

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Information Modeling and Relational Databases, Second Edition (The Morgan Kaufmann Series in Data Management Systems) Review

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(More customer reviews)Everyone needs this book. Read more to find out why:
If you intend to create genuinely useful business applications without first creating an accurate conceptual data model and deriving the database schema from the model, then I hope your projects have very large budgets and flexible deadlines, because you'll need both. Accurate conceptual data models are not an academic curiousity, they are a practical necessity. Well designed databases are the heart of every business application, and accurate conceptual data models are the foundation of every well designed database.
This book presents a method for data modeling called Object Role Modeling (ORM). If you've never created a data model before, you might as well learn the best method from the start. If you've used E-R (Entity Relationship) modeling before, this is your chance to learn a method that overcomes the limitations of E-R, while building on the knowledge you already have.
ORM is based on facts (assertions about the business sphere you are modeling), not entities and attributes. Business users understand facts much better than they understand data modeling abstractions. By using ORM facts, you create your data model in a language that business users can understand and validate. Poor communication with business users and inadequate understanding of requirements are major causes of design deficiencies. ORM solves these issues through its fact based approach.
ORM is also much more expressive than any other popular data modeling notation, ncluding UML and all major flavors of E-R. Many business rules should be expressed as data constraints, but traditional data modeling languages don't do well at capturing these constraints. By capturing the constraints in an ORM model and validating with the users, you make the construction of a good application much easier.
Halpin is an excellent writer, and this book is very easy to read. The many examples and crisp writing style mean that you'll actually understand what the author intends, a refreshing change from most computer books. If you've read the previous edition of this book, this update is very worthwhile. There is a lot of expanded and new material, and you'll be happy you purchased the new edition.

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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 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. * The book's associated web site provides answers to exercises, appendices, advanced SQL queries, and links to downloadable ORM tools.

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