Team :

• Ahmed Ibrahim => [email protected] github => https://github.com/Ahmed-Ibrahim-30
  
• Samaa Khalifa Elsayed => [email protected] github => https://github.com/SamaaKhalifa
  
• Noura Ashraf AbdElnaby => [email protected] github => https://github.com/NouraAshraff
  
• Sondos Emara Gomaa Basha => [email protected] github => https://github.com/SondosEmara
  

University-Expert-System

● This project introduce an expert university system 
and the different relations between its parts represented as facts
and rules in clips and hierarchy ontology in protégé.
It also discusses how to infer on it using rule based system “clips” 
and SparQl query language.

University-Expert-System has the Following Classes:

• University
• Faculty
• Department
• Program (Module)
• Course
• academic staff
• Exams
• Course work
• Thesis
• Lecture hall
• Library
• Lab room
• Lecturer
• TA
• Student

Part1 (ontology):

⦁	Define the different classes and subclasses in the system using ontology.
⦁	Define the relations between classes using object property. 
⦁	Define the attributes of each class using data property.
⦁	Define the individuals (instance) of each class.
⦁	Reason on the whole ontology system to infers new data.
⦁	Use SparQl query language to extract new knowledge.

Ontology Diagram: Object Properties(Relationships), Data Property and Classes:
1 - Class (University)

 ⦁ Data properties: UniversityName.
 ⦁ Object properties: hasFaculty.

2 - Class (Faculty)

 ⦁ Data properties: FacultyName.
 ⦁ Object properties: hasPlaces ,hasDepartment and isInside.

3 - Class (Course)

 ⦁ Data properties: CourseName.
 ⦁ Object properties: hasExam , hasStudent, hasWork,isToughtBy and is_taught_in .

4 - Class (Course Work)

 ⦁ Data properties: workName.

5 - Class (Department)

 ⦁ Data properties: DepartmentName.
 ⦁ Object properties: hasLecturer and hasTA.

6 - Class (Faculty_Place)

 ⦁ Data properties: PlaceName.

7 - Class (Academic_Staff)

 ⦁ Object properties: hasThesis ,inDepartment  and teach.

8 - Class (Lecturer)

 ⦁ Data properties: LecturerName.

9 - Class (Lab_room)

10 - Class (Lecture_hall)

11 - Class (Library)

12 - Class (Student)

   ⦁ Data properties: GPA, level, studId and StudName.
   ⦁ Object properties: hasDepartment and study.

13 - Class (TA)

   ⦁ Data properties: TAName.
   ⦁ Object properties: inDept .

14 - Class (Thesis)

   ⦁ Data properties: TAName.

Part2 (clips):

⦁	Define the different classes and subclasses in the system using clips.
⦁	Define the relations between classes using rules. 
⦁	Define the individuals (instance) of each class.
⦁	Create functions to be able to infer on data.
⦁	Use clips rule based system to extract new knowledge.

Graphical user Interface

• Choose the query to run from the following:
  

• Get all TAs belonging to a department.
  
  Result :) ^^
  

• Get the courses a student is currently studying.
  
  Result :) ^^
  

• Get all the courses offered by a certain faculty.
  
  Result :) ^^
  

• Get Lecturers of a faculty.
  
  Result :) ^^
  

• Get all faculties of a university.
  
  Result :) ^^