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The Palestinian eGovernment Academy
www.egovacademy.ps
Tutorial 1: Data and Business Process Modeling
Session 1.3
Conceptual Analyses
Prof. Mustafa Jarrar
Sina Institute, University of Birzeit
mjarrar@birzeit.edu
www.jarrar.info
Reviewed by
Prof. Marco Ronchetti, Trento University, Italy
PalGov © 2011 1
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
2
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.
PalGov © 2011 3
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:
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 Analyses
• Given an application domain, e.g. hospital, and three information
modelers, what steps do you suggest they start with, to build the
hospital‟s conceptual model?
• There is no strict or perfect modeling process or procedure!
• You may start with any step you think suitable, taking into account the
complexity of the domain, available resources, modelers‟ prior
knowledge about the domain, etc.
• It is recommended that you modularize the domain into sub-domains,
build a conceptual schema for each sub-domain, then integrate all sub-
schemes into one conceptual schema.
• The following procedure (7 steps) is to help you model a sub-domain,
but you don‟t have to strictly follow these steps.
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7. 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
PalGov © 2011 7
8. Elementary Facts and Fact Types
What is a fact?
– Rami smokes.
– Rami drives car.
– Rabab was born in Ramallah.
– Rami smokes and drives car.
– If Rabab was born in Ramallah and Ramallah is part of
Palestine, then Rabab was born in Palestine.
A fact must be either true or false
What is a fact type?
– Person smokes.
– Person drives car.
– Person was born in a city.
– Person smokes and drives car.
– If a Person was born in a city and this City is part of a
country, then this person was born in that country.
PalGov © 2011 8
9. Elementary Facts and Fact Types
What is an elementary fact type?
– Person smokes.
– Person drives car.
– Person was born in a city.
– Person smokes and drives car.
– If a Person was born in a city and this City is part of
a country, then this person was born in that country.
An elementary fact type cannot be split.
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11. 1. Make elementary facts from examples
• Mustafa teaches Knowledge Engineering.
• Rami is enrolled in Knowledge Engineering.
• Knowledge Engineering is offered by the University of Birzeit.
From examples to fact types
The person that has the name Mustafa teaches the course that has the title
Knowledge Engineering.
The person that has the name Rami is enrolled in the course that has the title
Knowledge Engineering.
The course that has the title Knowledge Engineering is offered by the
university that has the name University of Birzeit.
More precise
The person (ID4514) that has the name Mustafa teaches the course (SC242)
that has the title Knowledge Engineering.
The person (ID123) that has the name Rami is enrolled in the course (CS242)
that has the title Knowledge Engineering.
The course (CS242) that has the title Knowledge Engineering is offered by the
university that has the name University© 2011
of Birzeit.
PalGov 11
12. Conceptual Schema Design Steps
1. From examples to elementary facts
2. Draw fact types and apply population check
PalGov © 2011 12
13. 2. Draw fact types and apply population check
The Person (ID4514) that has the name Mustafa teaches the course (SC242)
that has the title Knowledge Engineering.
The Person (ID123) that has the name Rami is enrolled in the course (CS242)
that has the title Knowledge Engineering.
The course (CS242) that has the title Knowledge Engineering is offered by the
university that has the name University of Birzeit.
Draw Fact Types
Has/IsOf
Teaches/ Title
IsOf/Has OfferedBy /Offers
Person Course University
Name (Code)
(nr) (Name)
EnrolledIn/
PalGov © 2011 13
14. 2. Draw fact types and apply population check
The Person (ID4514) that has the name Mustafa teaches the course (SC242)
that has the title Knowledge Engineering.
The Person (ID123) that has the name Rami is enrolled in the course (CS242)
that has the title Knowledge Engineering.
The course (CS242) that has the title Knowledge Engineering is offered by the
university that has the name University of Birzeit.
Test with population
Has/IsOf
Teaches/ Title
SC242 Knowledge Engineering
IsOf/Has ID4154 SC242 OfferedBy /Offers
Person Course University
Name (Code)
(nr) (Name)
EnrolledIn/
Mustafa ID4154 SC242 Birzeit University
Rami ID123 ID123 SC242
PalGov © 2011 14
15. Basic ORM Constructs and Syntax
• Object and Value Types
• Roles and relations
• Unary relations
• Ternary relations
• Nested Fact Types
• Ring Fact Types
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16. Object and Values Types
Person Car
drives
Person Car
Adams B 235PZN
Jones E 235PZN
Jones E 108AAQ has has
„Adams B‟ „235PZN‟
„Jones E‟ „108AAQ‟
PersonName RegNr
Object Type (non lexical)
You cannot lexicalize, or refer to a
drives / is driven by
person without using a value of
its properties. Person Car
has has
Value Type (lexical)
refers to refers to
It is always a value of an
Object Type.
PersonName
PalGov © 2011
RegNr
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17. Roles and Relations
Called Binary Relation
It consists of two roles
(“drives” and “is driven by”)
Called Role
which is part of a relation
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18. Unary Relations
Pat smokes
Lee smokes
Shir does not smoke
Called Unary Relation
as it has one role
(“smokes”)
You can transform unary fact types into binary:
PalGov © 2011 18
20. Nested Fact Types
Called Nested Fact Type
The fact type “Student enrolled in
Subject” is objectified, i.e., the whole
Fact type is seen as an Object Type
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21. Ring Fact Types
Same object type is connected to two roles in the same relation
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22. The ORM Syntax (Test)
An object type can be only connected with roles.
Each role can be connected with only one object type.
PalGov © 2011 22
23. References
1. Information Modeling and Relational Databases: From
Conceptual Analysis to Logical Design, Terry Halpin (ISBN 1-
55860-672-6) – Chapter 3.
PalGov © 2011 23