1 x 110-minute lecture weekly
1 x 1-hour tutorial weekly
1 x 3-hour computer lab weekly
Enrolment not permitted
COMP4706 has been successfully completed
Assumed knowledge
Computing skills such as acquired in introductory computing and database topics and programming knowledge and skills such as acquired in second year topics.
Topic description
Advanced Conceptual Modelling extends the traditional database modelling practices to advanced database paradigms to those that will be common in the future while the knowledge engineering material focuses on new areas of study in the knowledge management and knowledge engineering areas.

Temporal, Spatial and Spatio-Temporal Databases (Concepts, Transaction v. Valid time, Historical v. Rollback v. Temporal databases, Geographic databases, spatio-temporal database query languages, implementation issues); Schema Evolution (relationship between schema evolution and temporal databases, information capacity, issues, changing data - strict v. lazy v. no conversion, partial v. full evolution); Active Data Models (concept, triggers, rules, functions); Object-oriented Data Models (concepts, polymorphism, encapsulation, methods and state, hierarchies and inheritance, object-relational v. pure object-oriented databases query languages); Deductive databases (origins and concepts, knowledge representation, inference rules, recursion); Semi-structured Models and Web-based databases (concept, XML family of standards, schema models); Managing Ontologies.
Educational aims
On successful completion of this topic, a student is expected to be able to:
  1. Appraise the advantages and limitations of various advanced data modelling and knowledge management paradigms
  2. Identify the potential and limitations of various research efforts in conceptual modelling and knowledge engineering
  3. Identify and apply techniques applicable to advanced database and knowledge engineering models
  4. Explain the basis for the development of expert database systems
  5. Plan, carry out, and report on a research-oriented project in the area
Expected learning outcomes
At the completion of this topic, students are expected to be able to:

  1. Evaluate the advantages and limitations of different data modelling techniques
  2. Interpret and critically analyse research papers on conceptual modelling and knowledge engineering
  3. Prepare and present reports on aspects of conceptual modelling and knowledge engineering
  4. Construct an expert database system