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Data Base Systems



Database Management Systems (DBMS) are vital components of modern

information systems. Database applications are pervasive and range in size

from small in-memory databases to terra bytes or even larger in various appli-

cations domains. The course focuses on the fundamentals of knowledgebase

and relational database management systems, and the current developments

in database theory and their practice.

Course Description


The course reviews topics such as conceptual data modelling, relational data

model, relational query languages, relational database design and transac-

tion processing and current technologies such as semantic web, parallel and

noSQL databases. It exposes the student to the fundamental concepts and

techniques in database use and development as well provides a foundation

for research in databases.

The course assumes prior exposure to databases, specically to the rela-

tional data model and it builds new technologies on this foundation. In the

rst half of the course the relational data model, relational query languages,

relational database design and conceptual data modeling are reviewed. It

then focuses on XML, RD, OWL, parallel, and noSQL databases. It also

bridges databases and knowledgebases which is the current trend.

The course requires a term project in which the student implements a

database application or explores a database issue.

We will use PostgresSQL as the database platform for doing the assign-



Topic List


Topics can include but are not limited to:

  • Database concepts
  • Relational model
  • Relational query languages

              -Relational Algebra and Calculus




  • Triggers
  • Embedded SQL
  • Recursion
  • Web database programming
  • Conceptual data modeling
  • E/R data model
  • OO data model
  • Relational database design

                 -Normal Forms (NF)


                -Lossless join decomposition

  • XML, XPath and XQuery
  • Ontology and Data Model
  • Semantic Web
  • RDF, RDF Schema, and OWL
  • Storage and indexing
  • Query processing and optimization
  • Parallel and distributed databases
  • NoSQL databases
  • Transaction processing and database recovery
  • Database security
  • Current developments in knowledgebase
  • Big data and Hadoop.


Learning Goals


The course content is balanced on theory and practice, the course aims at

achieving the following learning outcomes:

An appreciation of pervasive use of Knowledgebase and DBMS in dif-

ferent application domains

  • Skill for developing database applications
  • Skills for devising data models and query languages
  • Skills for developing web database applications
  • Learning storage and indexing of data
  • Learning transaction processing and database recovery
  • Learning knowledge representation and semantic web technologies
  • Skills to integrate knowledge to databases



Class participations, discussions and attendance are a critical component of

the course and accounts 10

Written assignments will provide the students the opportunity to appre-

ciate the theoretical underpinnings of the databases systems and comprise

20% of the term grade. These are on data modeling (Entity/Relationship

data model), query languages (Relational Algebra and Relational Calculus),

database design, and Resource Denition Framework or Ontology Web Lan-

guage for knowledge representation.

Two programming assignments and a term project will provide the op-

portunity for the students to develop technical skills and comprise 20% of the

term grade. The rst project is on Structured Query Language and the sec-

ond one is on the web database programming. The database project involves

a complete database application development from design to implementation

or a deeper investigation of a topic in databases and knowledgebases.

A mid-term and a nal exam, each is 25%. Individual Assignments or

Quizzes 20% Term Projects 15% Midterm Exams 30% Final Exam 35%