Jarrar: Conceptual Schema Design Steps

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Lecture slides by Mustafa Jarrar at Birzeit University, Palestine.
See the course webpage at: http://jarrar-courses.blogspot.com/2011/09/knowledgeengineering-fall2011.html and http://www.jarrar.info

and on Youtube:
http://www.youtube.com/watch?v=3_-HGnI6AZ0&list=PLDEA50C29F3D28257

Lecture Notes Knowledge Engineering (Ch3)

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Jarrar: Conceptual Schema Design Steps

  1. 1. 1Jarrar © 2015 Conceptual Analyses Conceptual Schema Design Steps (Chapter 3) Reference: Mustafa Jarrar: Lecture Notes on Conceptual Analyses Birzeit University, Palestine, 2015 Mustafa Jarrar Birzeit University, Palestine mjarrar@birzeit.edu www.jarrar.info
  2. 2. 2Jarrar © 2015 Watch this lecture and download the slides from http://jarrar-courses.blogspot.com/2015/01/dataandbusinessprocessmodelling.html Some diagrams in this lecture are based on [1]
  3. 3. 3Jarrar © 2015  Part 1: Conceptual Analyses Steps  Part 2: Basic ORM Constructs and Syntax  Part 3: Use case (ID Card)  Part 4: Use case (University Programs) Mustafa Jarrar: Lecture Notes on Data & Business Process Modeling, University of Birzeit, Palestine, 2015 Conceptual Analyses Conceptual Schema Design Steps
  4. 4. 4Jarrar © 2015 Conceptual Analyses Given an application domain, e.g. hospital, and three information modelers, what steps do you suggest them to 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.
  5. 5. 5Jarrar © 2015 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
  6. 6. 6Jarrar © 2015 Elementary Facts and Fact Types – 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. What is a fact type? 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
  7. 7. 7Jarrar © 2015 Elementary Facts and Fact Types – 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. What is an elementary fact type?       An elementary fact type cannot be spited.
  8. 8. 8Jarrar © 2015 1. From examples to elementary facts Conceptual Schema Design Steps
  9. 9. 9Jarrar © 2015 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.  The Person (ID4514) that has the name Mustafa teaches the course (SC242) that has the title Knowledge Engineering.  The Person (ID123) Rami is enrolled in the course (CS242) that has the 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.  The Person that has the name Mustafa teaches the course that has the title Knowledge Engineering.  The Person Rami is enrolled in the course that has the 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 From examples to fact types
  10. 10. 10Jarrar © 2015 1. From examples to elementary facts 2. Draw fact types and apply population check Conceptual Schema Design Steps
  11. 11. 11Jarrar © 2015 2. Draw fact types and apply population check University (Name) Person (nr) Course (Code) IsOf/Has Name TitleTeaches/ EnrolledIn/ Has/IsOf OfferedBy /Offers  The Person (ID4514) that has the name Mustafa teaches the course (SC242) that has the title Knowledge Engineering.  The Person (ID123) Rami is enrolled in the course (CS242) that has the 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
  12. 12. 12Jarrar © 2015 2. Draw fact types and apply population check Person (nr) Course (Code) IsOf/Has Name TitleTeaches/ EnrolledIn/ Has/IsOf  The Person (ID4514) that has the name Mustafa teaches the course (SC242) that has the title Knowledge Engineering.  The Person (ID123) Rami is enrolled in the course (CS242) that has the 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 Mustafa ID4154 Rami ID123 SC242 Knowledge Engineering SC242 Birzeit University ID4154 SC242 ID123 SC242 University (Name) OfferedBy /Offers
  13. 13. 13Jarrar © 2015  Part 1: Conceptual Analyses Steps  Part 2: Basic ORM Constructs and Syntax  Part 3: Use case (ID Card)  Part 4: Use case (University Programs) Mustafa Jarrar: Lecture Notes on Data & Business Process Modeling, University of Birzeit, Palestine, 2015 Conceptual Analyses Conceptual Schema Design Steps
  14. 14. 14Jarrar © 2015 Basic ORM Constructs and Syntax • Object and Value Types • Roles and relations • Unary relations • Ternary relations • Nested Fact Types • Ring Fact Types
  15. 15. 15Jarrar © 2015 Object and Values Types Person Car Adams B 235PZN Jones E 235PZN Jones E 108AAQ Person has PersonName Car RegNr refers to has refers to drives / is driven by ‘Adams B’ ‘Jones E’ ‘235PZN’ ‘108AAQ’ drives CarPerson has has PersonName RegNr Value Type (lexical) It is always a value of an Object Type. Object Type (non lexical) You cannot lexicalize, or refer to a person without using a value of its properties.
  16. 16. 16Jarrar © 2015 Roles and Relations Called Binary Relation It consists of two roles (“drives” and “is driven by”) Called Role which is part of a relation Called Role which is part of a relation
  17. 17. 17Jarrar © 2015 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:
  18. 18. 18Jarrar © 2015 Ternary Relations Called Ternary Relation as it has three roles (“smokes”)
  19. 19. 19Jarrar © 2015 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
  20. 20. 20Jarrar © 2015 Ring Fact Types Same object type is connected to two roles in the same relation
  21. 21. 21Jarrar © 2015 The ORM Syntax (Test) An object type can be only connected with roles. Each role can be connected with only one object type.            
  22. 22. 22Jarrar © 2015  Part 1: Conceptual Analyses Steps  Part 2: Basic ORM Constructs and Syntax  Part 3: Use case (ID Card)  Part 4: Use case (University Programs) Mustafa Jarrar: Lecture Notes on Data & Business Process Modeling, University of Birzeit, Palestine, 2015 Conceptual Analyses Conceptual Schema Design Steps
  23. 23. 23Jarrar © 2015 Use Case (ID Card) Model the Information found in your ID Card, using ORM, for example: Each Person has a ID Number, First Name, Father Name, Grandfather Name, BirthDate, Birth Place, Religion, Gender, and Address. A Person maybe a father/mother of one or more persons, and wife/husband of another person. etc. • Each student is expected to deliver (PDF and Hard copies) of his/her ORM model before (Deadline: 17/2/2015). • Any ORM tool can be used. • Each student is expected to bring his laptop next lecture, so to present his/her models to all students.
  24. 24. 24Jarrar © 2015  Part 1: Conceptual Analyses Steps  Part 2: Basic ORM Constructs and Syntax  Part 3: Use case (ID Card)  Part 4: Use case (University Programs) Mustafa Jarrar: Lecture Notes on Data & Business Process Modeling, University of Birzeit, Palestine, 2015 Conceptual Analyses Conceptual Schema Design Steps
  25. 25. 25Jarrar © 2015 Use Case (University Programs) Model Information about University Programs, using ORM, for example: According to the Ministry of Higher Education: A University consists of a set of faculties, each faculty consists of departments, each department offers several Bachelor and Master programs. Each program consists of a set of courses. Same courses might not be offered by different programs. A course has number, title, description, etc. • Each student is expected to deliver (PDF and Hard copies) of his/her ORM model before (Deadline: 19/2/2015). • Any ORM tool can be used. • Each student is expected to bring his laptop next lecture, so to present his/her models to all students.
  26. 26. 26Jarrar © 2015 References 1. Terry Halpin, Tony Morgan: Information Modeling and Relational Databases, Second Edition. 2nd Edition. The Morgan Kaufmann Series in Data Management Systems. ISBN: 0123735688 2. Mustafa Jarrar and Stijn Heymans: Towards Pattern-Based Reasoning For Friendly Ontology Debugging. Journal of Artificial Intelligence Tools. Volume 17. No.4. World Scientific Publishing. Aug 2008. 3. Mustafa Jarrar: Mapping ORM Into The SHOIN/OWL Description Logic- Towards A Methodological And Expressive Graphical Notation For Ontology Engineering. In OTM 2007 workshops: Proceedings of the International Workshop on Object-Role Modeling (ORM'07). Pages (729-741), LNCS 4805, Springer. ISBN: 9783540768890. Portogal. November, 2007 4. Mustafa Jarrar: Towards Automated Reasoning On ORM Schemes. -Mapping ORM Into The DLR_idf Description Logic. In proceedings of the 26th International Conference on Conceptual Modeling (ER 2007). Pages (181-197). LNCS 4801, Springer. Auckland, New Zealand. ISBN 9783540755623. November 2007 5. Mustafa Jarrar and Stijn Heymans: Unsatisfiability Reasoning In ORM Conceptual Schemes. In Current Trends in Database Technology - EDBT 2006: Proceeding of the IFIP-2.6 International Conference on Semantics of a Networked. Pages (517-534). LNCS 4254, Springer. Munich, Germany. ISBN: 3540467882. March 2006. 6. Mustafa Jarrar, Maria Keet, and Paolo Dongilli: Multilingual Verbalization Of ORM Conceptual Models And Axiomatized Ontologies. Technical eport. STARLab, Vrije Universiteit Brussel, Feb 2006. 7. Mustafa Jarrar: Modularization And Automatic Composition Of Object-Role Modeling (ORM) Schemes. OTM 2005 Workshops: Proceedings of the Object-Role Modeling (ORM'05). Pages (613- 625). LNCS 3762, Springer. Larnaca, Cyprus. ISBN: 3540297391. November 2005.

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