pal gov.tutorial1.session3 1.uniquenessrules

1PalGov © 2011

أكاديمية الحكومة اإللكترونية الفلسطينية

The Palestinian eGovernment Academy

www.egovacademy.ps

Session 3.1

Uniqueness Rules

Tutorial 1: Data and Business Process Modeling

Prof. Mustafa Jarrar

Sina Institute, University of Birzeit

mjarrar@birzeit.edu

www.jarrar.info

Reviewed by

Prof. Marco Ronchetti, Trento University, Italy

2PalGov © 2011

About

This tutorial is part of the PalGov project, funded by the TEMPUS IV program of the

Commission of the European Communities, grant agreement 511159-TEMPUS-1-

2010-1-PS-TEMPUS-JPHES. The project website: www.egovacademy.ps

University of Trento, Italy

University of Namur, Belgium

Vrije Universiteit Brussel, Belgium

TrueTrust, UK

Birzeit University, Palestine

(Coordinator )

Palestine Polytechnic University, Palestine

Palestine Technical University, PalestineUniversité de Savoie, France

Ministry of Local Government, Palestine

Ministry of Telecom and IT, Palestine

Ministry of Interior, Palestine

Project Consortium:

Coordinator:

Dr. Mustafa Jarrar

Birzeit University, P.O.Box 14- Birzeit, Palestine

Telfax:+972 2 2982935 mjarrar@birzeit.edu

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© Copyright Notes

this material, or part of it, but should properly useEveryone is encouraged to

(logo and website), and the author of that part. cite the project

in any form or by any reproduced or modified No part of this tutorial may be

from the project, who have the full written permissionmeans, without prior

copyrights on the material.

Attribution-NonCommercial-ShareAlike

CC-BY-NC-SA

This license lets others remix, tweak, and build upon your work non-

commercially, as long as they credit you and license their new creations

under the identical terms.

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Tutorial Map

Topic Time

Module I: Conceptual Data Modeling

Session 0: Outline and Introduction

Session 1.1: Information Modeling 1

Session 1.2: Conceptual Data Modeling using ORM 1

Session 1.3: Conceptual Analyses 1

Session 2: Lab- Conceptual Analyses 3

Session 3.1: Uniqueness Rules 1.5

Session 3.2: Mandatory Rules 1.5

Session 4: Lab- Uniqueness & Mandatory Rules 3

Session 5: Subtypes and Other Rules 3

Session 6: Lab- Subtypes and Other Rules 3

Session 7.1: Schema Equivalence &Optimization 1.5

Session 7.2: Rules Check &Schema Engineering 1.5

Session 8: Lab- National Student Registry 3

Module II: Business Process Modeling

Session 9: BP Management and BPMN: An Overview 3

Session 10: Lab - BP Management 3

Session 11: BPMN Fundamentals 3

Session 12: Lab - BPMN Fundamentals 3

Session 13: Modeling with BPMN 3

Session 14: Lab- Modeling with BPMN 3

Session 15: BP Management & Reengineering 3

Session 16: Lab- BP Management & Reengineering 3

Intended Learning ObjectivesModule 1 (Conceptual Date Modeling)

A: Knowledge and Understanding

11a1: Demonstrate knowledge of conceptual modeling notations and concepts

11a2: Demonstrate knowledge of Object Role Modeling (ORM) methodology.

11a3: Explain and demonstrate the concepts of data integrity & business rules

B: Intellectual Skills

11b1: Analyze application and domain requirements at the conceptual level,

and formalize it using ORM.

11b2: Analyze entity identity at the application and domain levels.

11b4: Optimize, transform, and (re)engineer conceptual models.

11b5: Detect &resolve contradictions & implications at the conceptual level.

C: Professional and Practical Skills

11c1: Using ORM modeling tools (Conceptual Modeling Tools).

Module 2 (Business Process Modeling)

A: Knowledge and Understanding

12a1: Demonstrate knowledge of business process modeling notations and concepts.

12a2: Demonstrate knowledge of business process modeling and mapping.12a3: Demonstrate understand of business process optimization and re-engineering.

B: Intellectual Skills

12b1: Identify business processes.

12b2: Model and map business processes.

12b3: Optimize and re-engineer business processes.

C: Professional and Practical Skills

12c1: Using business process modeling tools, such as MS Visio.

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Session ILOs

After completing this session students will be able to:

11a3: Explain and demonstrate the concepts of data integrity and

business rules.

11b1: Analyze application and domain requirements at the

conceptual level, and formalize it using ORM.

11b2: Analyze entity identity at the application and domain levels.

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Conceptual Schema Design Steps

1. From examples to elementary facts

2. Draw fact types and apply population check

3. Combine entity types

4. Add uniqueness constraints

5. Add mandatory constraints

6. Add set, subtype, & frequency constraints

7. Final checks, & schema engineering issues

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Uniqueness Constraint

For each state taken individually, each person has at most one weight.

How can we record such information without redundancy?

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Uniqueness on Unary Fact Types

Is their any problem with this schema?

How can we prevent people from adding such redundant information?

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Uniqueness on Unary Fact Types

The uniqueness constraint

ensures entities are

unique (no duplicates)

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Uniqueness on Binary Fact Types

Each Politician was born

in at most one Country

Each Country has at

most one head Politician

Each Politician heads

government of at most

one Country

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Uniqueness on Binary Fact Types

Who can give more examples?

Means many to many

It is possible that the same Politician visited more than one Country

and that the same Country was visited by more than one Politician

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Uniqueness on Binary Fact Types

What is unique here?

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Uniqueness on Binary Fact Types

What is unique here?

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Uniqueness on Binary Fact Types

No duplicates are allowed in a's column

Each a R's at most one b

No duplicates are allowed in b's column

Each b is R'd by at most one a

Both the foregoing constraints apply

No duplicate (a,b) rows are allowed

Each a may R many bs and vice versa

The four uniqueness constraint patterns for a binary fact type:

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How to think about Uniqueness

Is the population significant?

Adding counterexamples

to test the constraints

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Uniqueness on Binary Fact Types

Which is more realistic?

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Uniqueness on Ternary Fact Types

What are the uniqueness constraints?

Each (Person, Subject) combination is unique.

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Uniqueness on Ternary Fact Types

Allowed basic uniqueness constraints for a ternary fact type:

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Uniqueness on Ternary Fact Types

What does this uniqueness mean?

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Uniqueness on Ternary Fact Types

Allowed uniqueness constraint combinations for a ternary fact type:

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Uniqueness on Ternary Fact Types

Which of these constraint patterns is illegal? Why?

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Example of Uniqueness on n-ary fact types

Each (a,c,d) combination occurs in at most one row.

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Uniqueness with Nested Fact Types

Explain what is unique

This constraint is particularly

important! Why?

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What is the difference between these?

Explain the joins

Do we need uniqueness?

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External Uniqueness constraints

What is missing?

u

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External Uniqueness constraints

The meaning of the External Uniqueness

Each (b,c) combination is paired with at most one a

Each population R join S has bc unique

(where “join” denotes “conceptual inner join”)

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Example with nest fact types

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Key Length Check

What is wrong?

Splits into

Each UC in an elementary n-ary relationship must

span at least n-1 roles

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Key Length Check

Splits into

What is wrong?

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Discussion

Summarize what you learnt until now?

Problems of uniqueness in your daily life?

Compare the uniqueness constraint in ORM

with the cardinality constraints in UML and EER?

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References

1. Information Modeling and Relational Databases: From Conceptual Analysis to Logical Design, Terry Halpin (ISBN 1-55860-672-6) – Chapter 4.