1. ‫أكاديمية الحكومة اإللكترونية الفلسطينية‬
The Palestinian eGovernment Academy
www.egovacademy.ps
Tutorial 1: Data and Business Process Modeling
Session 5
Subtype Relations and Other Constraints
Prof. Mustafa Jarrar
Sina Institute, University of Birzeit
mjarrar@birzeit.edu
www.jarrar.info
Reviewed by
Prof. Marco Ronchetti, Trento University, Italy
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2. 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
Project Consortium:
Birzeit University, Palestine
University of Trento, Italy
(Coordinator )
Palestine Polytechnic University, Palestine Vrije Universiteit Brussel, Belgium
Palestine Technical University, Palestine
Université de Savoie, France
Ministry of Telecom and IT, Palestine
University of Namur, Belgium
Ministry of Interior, Palestine
TrueTrust, UK
Ministry of Local Government, Palestine
Coordinator:
Dr. Mustafa Jarrar
Birzeit University, P.O.Box 14- Birzeit, Palestine
Telfax:+972 2 2982935 mjarrar@birzeit.eduPalGov © 2011
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3. © Copyright Notes
Everyone is encouraged to use this material, or part of it, but should properly
cite the project (logo and website), and the author of that part.
No part of this tutorial may be reproduced or modified in any form or by any
means, without prior written permission from the project, who have the full
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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4. Tutorial Map
Intended Learning Objectives
Topic Time
Module 1 (Conceptual Date Modeling)
Module I: Conceptual Data Modeling
A: Knowledge and Understanding
11a1: Demonstrate knowledge of conceptual modeling notations and concepts Session 0: Outline and Introduction
11a2: Demonstrate knowledge of Object Role Modeling (ORM) methodology. Session 1.1: Information Modeling 1
11a3: Explain and demonstrate the concepts of data integrity & business rules Session 1.2: Conceptual Data Modeling using ORM 1
B: Intellectual Skills Session 1.3: Conceptual Analyses 1
11b1: Analyze application and domain requirements at the conceptual level, Session 2: Lab- Conceptual Analyses 3
and formalize it using ORM. Session 3.1: Uniqueness Rules 1.5
11b2: Analyze entity identity at the application and domain levels. Session 3.2: Mandatory Rules 1.5
11b4: Optimize, transform, and (re)engineer conceptual models. Session 4: Lab- Uniqueness & Mandatory Rules 3
11b5: Detect &resolve contradictions & implications at the conceptual level. Session 5: Subtypes and Other Rules 3
C: Professional and Practical Skills Session 6: Lab- Subtypes and Other Rules 3
11c1: Using ORM modeling tools (Conceptual Modeling Tools). Session 7.1: Schema Equivalence &Optimization 1.5
Module 2 (Business Process Modeling) Session 7.2: Rules Check &Schema Engineering 1.5
A: Knowledge and Understanding Session 8: Lab- National Student Registry 3
12a1: Demonstrate knowledge of business process modeling notations and concepts.
Module II: Business Process Modeling
12a2: Demonstrate knowledge of business process modeling and mapping.
12a3: Demonstrate understand of business process optimization and re-engineering. Session 9: BP Management and BPMN: An Overview 3
B: Intellectual Skills Session 10: Lab - BP Management 3
12b1: Identify business processes. Session 11: BPMN Fundamentals 3
12b2: Model and map business processes. Session 12: Lab - BPMN Fundamentals 3
12b3: Optimize and re-engineer business processes. Session 13: Modeling with BPMN 3
C: Professional and Practical Skills Session 14: Lab- Modeling with BPMN 3
12c1: Using business process modeling tools, such as MS Visio. Session 15: BP Management & Reengineering 3
Session 16: Lab- BP Management & Reengineering 3
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5. 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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6. 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 subtype relations and other constraints
7. Final checks, & schema engineering issues
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7. Outline
• Quick Math background
• Value Constraints
• Set Constrains
o Subset
o Equality
o Exclusion
• Subtype relations
• Frequency constraints
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8. Mathematical Background
Hypothetical Euler diagrams for set comparisons.
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9. Mathematical Background
Venn diagrams for three set-forming operations.
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10. Mathematical Background
Venn diagrams for (a) A is a proper subset of B and (b) four sets.
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11. Outline
• Quick Math background
• Value Constraints
• Set Constrains
o Subset
o Equality
o Exclusion
• Subtype relations
• Frequency constraints
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12. Value Constraint
Called Value Constraint
A set of values, from
which the value of
the MedalKind is
limited to
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13. Value Constraint
The value of sex should be one of {„M‟, „F‟}
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14. Value Constraint
Value constraints may list the possible values of a value type.
 Who can give more examples?
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15. Outline
• Quick Math background
• Value Constraints
• Set Constrains
o Subset
o Equality
o Exclusion
• Subtype relations
• Frequency constraints
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16. Role subset/equality constraint
Subset constraint: Equality constraint:
Every Member booked an Hour Every Member „has‟ ReactionTime
should play sport. should „has‟ HeartRate, and every
Member „has‟ HeartRate should
„has‟ ReactionTime.
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17. Role subset constraint
Notice that this subset constraint is
implied, and should be removed.
That is, there is no need to say that every A
playing r2 must also play r1 (subset), because the
mandatory constraint here means that every A
must play r1 (the Mandatory implies the subset).
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18. Role equality constraint
Also this quality constraint is implied,
and should be removed.
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19. Implication
Who can explain the difference?
The two constraints in the first model say: each A must play r1 or r2 (or
both), and that if A plays r2 then it must play r1. This means that r1 must
be always played (which is the second model)
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20. Role Exclusion Constraint
Exclusion constraint:
Every Employee is allocated a
ParkingSpace should not claim
MoneyAmt.
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21. Role Exclusion Constraint
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22. Role Exclusion Constraint
Each partner must be either a husband
or wife (but not both at the same time).
Called “Exclusive-or”
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23. Exclusive-or (another example)
Each Account must be
OwnedBy a Person or a
Company, but not both.
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24. Role Exclusion Constraint
Each person has at most one of three vices. i.e., from 0 to 3 vices.
It can be written also as
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25. Pair Exclusion Constraint
How can we restrict that a
person can drive a car only if
he owns that car.
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26. Pair-subset constraint
An example of a tuple-subset constraint between sequences of three roles.
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27. Equality Constraint
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28. Pair Exclusion Constraint
Can the same person „own‟ and „wants to buy‟ the same car?
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29. What is Wrong?
    
Implies Implies Implies
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30. Outline
• Quick Math background
• Value Constraints
• Set Constrains
o Subset
o Equality
o Exclusion
• Subtype relations
• Frequency constraints
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31. Subtypes
Person
Male Female
• Generalization/Specialization hierarchy.
• A subtype inherits the properties of its supertype.
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32. Subtypes
Person
*
Australian Female
Female
Australian
* The indirect subtype connection is implied, so it should be omitted
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33. Subtypes
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34. Subtypes
Person
Person Person
Male Female Male Female Male Female
There is no person that Every person must be a Every person must be
can be Male and Female Male or a female. either a Male or a Female
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35. Subtypes
What is
Inherited?
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36. What is Wrong?
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37. Outline
• Quick Math background
• Value Constraints
• Set Constrains
o Subset
o Equality
o Exclusion
• Subtype relations
• Frequency constraints also called “Occurrence constraints”
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38. Frequency constraints
To indicate that each entry in a fact column must occur there exactly n
times, the number n is written beside the role.
Each city in the first
column must occur each drive kind in the
three times. Second column must
appear there twice
A compound transaction is needed to initially populate this fact type
requiring at least six facts to be added.
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39. Frequency constraints
n
A r
Each member of pop(r) occurs there exactly n times.
n must be a positive integer.
1
A r A r
If n = 1, this is equivalent to a uniqueness constraint
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40. Compound Frequency Constraint
The values of (Year and City) must occur exactly three times
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41. Ranged Frequency Constraint
Examples of minimum and maximum frequency constraints.
Each name of panel must occur at least 4
and at most 7 times. That is, each panel
must include 4 to 7 experts
Each expert can referee 5 papers
Each paper can be refereed by at least two experts.
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42. Discussion
Summarize what you learned? And what you think about it?
Compare what you learned with EER and UML?
Questions & Suggestions?
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43. References
1. Information Modeling and Relational Databases: From
Conceptual Analysis to Logical Design, Terry Halpin (ISBN 1-
55860-672-6) – Chapter 6.
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