COMP SCI 4094 - Distributed Databases and Data Mining

North Terrace Campus - Semester 2 - 2020

Topics covered in this course include: Distributed database system architecture, Distributed database system design, Distributed query processing and optimisation, Distributed transaction management, Data warehousing and OLAP technology, Association analysis, Classification and prediction, Cluster analysis, Mining complex types of data.

  • General Course Information
    Course Details
    Course Code COMP SCI 4094
    Course Distributed Databases and Data Mining
    Coordinating Unit Computer Science
    Term Semester 2
    Level Undergraduate
    Location/s North Terrace Campus
    Units 3
    Contact Up to 2 hours per week
    Available for Study Abroad and Exchange Y
    Prerequisites COMP SCI 2201
    Incompatible COMP SCI 4194
    Assumed Knowledge Knowledge of database systems as taught in COMP SCI 2207
    Assessment Written exam and/or assignments
    Course Staff

    Course Coordinator: Dr Wei Zhang

    Course Timetable

    The full timetable of all activities for this course can be accessed from Course Planner.

  • Learning Outcomes
    Course Learning Outcomes
    On completion of this course, students should:
    1. Explain distributed database systems architecture and design 
    2. Apply methods and techniques for distributed quey processing and optimisation
    3. Explain the broad concepts of distributed transaction process
    4. Discuss the basic concepts of Data warehousing and OLAP technology
    5. Apply methods and techniques for association analysis, data classification and clustering
    University Graduate Attributes

    This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:

    University Graduate Attribute Course Learning Outcome(s)
    Deep discipline knowledge
    • informed and infused by cutting edge research, scaffolded throughout their program of studies
    • acquired from personal interaction with research active educators, from year 1
    • accredited or validated against national or international standards (for relevant programs)
    Critical thinking and problem solving
    • steeped in research methods and rigor
    • based on empirical evidence and the scientific approach to knowledge development
    • demonstrated through appropriate and relevant assessment
    Teamwork and communication skills
    • developed from, with, and via the SGDE
    • honed through assessment and practice throughout the program of studies
    • encouraged and valued in all aspects of learning
    Career and leadership readiness
    • technology savvy
    • professional and, where relevant, fully accredited
    • forward thinking and well informed
    • tested and validated by work based experiences
    Intercultural and ethical competency
    • adept at operating in other cultures
    • comfortable with different nationalities and social contexts
    • able to determine and contribute to desirable social outcomes
    • demonstrated by study abroad or with an understanding of indigenous knowledges
    Self-awareness and emotional intelligence
    • a capacity for self-reflection and a willingness to engage in self-appraisal
    • open to objective and constructive feedback from supervisors and peers
    • able to negotiate difficult social situations, defuse conflict and engage positively in purposeful debate
  • Learning Resources
    Required Resources
    Text 1:
    M. T. Oszu and P. Valduriez, Principles of Distributed Database Systems, 2nd ed.,
    Prentice-Hall, 1999.

    Text 2:
    J. Han and M. Kamber, Data Mining: Concepts and Techniques, Morgan Kaufmann, 2000.

    Recommended Resources
    Additional materials posted on the course homepage:
    Online Learning
  • Learning & Teaching Activities
    Learning & Teaching Modes
    There are two lectures per week. There are weekly office hours/discussion sessions for student questions and technical assistance for digesting the technical contents delivered at lectures. We will also use 10 additional hours for student term project presentations.

    The information below is provided as a guide to assist students in engaging appropriately with the course requirements.

    On average, students are expect to spend around 12 hours a week on this course, including lectures,  doing the required readings, working on the programming assignments and term project.

    Learning Activities Summary
    Topics covered in this course include
    • Distributed database system architecture
    • Distributed database system design
    • Distributed query processing and optimization
    • Distributed transaction management
    • Data warehousing and OLAP technology
    • Association analysis
    • Classification and prediction
    • Cluster analysis
    Assignments will broadly follow the content of these topics

    Term project will allow students to choose a topic that is significant both in the current research trends and also to individual interest. 

    Specific Course Requirements
    There are no specific requirements for this course beyond prerequisite knowledge, attendence to the lectures, and the ability to work on the group programming assignments and the term project.
    Small Group Discovery Experience
    Small group discovery experience is acquired through intensive collaboration in the programming assignments and term project in groups of size 2-3.
  • Assessment

    The University's policy on Assessment for Coursework Programs is based on the following four principles:

    1. Assessment must encourage and reinforce learning.
    2. Assessment must enable robust and fair judgements about student performance.
    3. Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
    4. Assessment must maintain academic standards.

    Assessment Summary
    ·      Two programming assignment: 30%

    ·      Written term project report: 40%

    You will carry a term project for this course
    and submit a project report that will contribute towards 40% of your final
    grade. Half of this will be for the survey part, and the other half for the
    research part. The term project can be carried out individually, or in a group
    of two people. It is advisable that you should start your term project as soon
    as possible, in order to work out a satisfactory project report.

    The term project report will be assessed mainly on your understanding of the problem
    that your project is tackling, insight into its solution and strategies for its
    solution. Other factors that will be taken into consideration in the assessment
    include the organization, technical writing of the report, and cohesion of
    different components in the report.

    ·      Term project presentation: 20%

    You are required to make a 15-minute presentation of your term project. In case if your project is done in a group of two people, each group member is required to present the part of the project
    that contains his/her own work.

    The assessment for this item will be given based on the preparation of your
    presentation materials, delivery of the presentation, and understanding to the
    technical contents of your work.

    ·      Class performance: 10%

    This is the assessment to your understanding to the course contents through class questions, discussion and individual meetings.
    Assessment Related Requirements
    Students are expected to read a wide range of research papers relevant to the chisen topic of term project.
    Assessment Detail
    There are two programming assignment, one for distributed databases component and the other for data
    mining component. Each assignment is weighted 15% of the whole course assessment. Assignment 1 will be given (uploaded to course website and Forums) in week 2 and due in week 7. Assignment 2 will be given in week 6 and due in week 10.

    There is a term project of weight 60%. The projects consists of picking up a research problem in either
    distributed databases or data mining from among the ones listed on the course webpage and working on its solution for the duration of this term. Student may also choose other topics, upon consent by the course convener, that are relevant to the course content and of interest to own research.

    The project report should show a good understanding of the problem (resulting in a survey part), insight into its solution and a well defined strategy for its solution. You should treat the term project as if you were doing the initial background study for further in-depth research. In other words, the report should demonstrate an understanding of and an insight into the problem such that given enough time, you could carry it to its logical conclusion and complete the research.

    The term project that you will carry out for this course consists of a project report and a project presentation. The project report will contribute towards 40% of your final grade. Half of this will be for the survey part, and the other half for the research part. The project could be individual, or in a group of two people. For group project submissions, both members of the group will receive the same grade for the
    project report. Therefore, it is incumbent upon you to make sure that both partners share in the work (and let me know very quickly if the partnership is not working). The project presentation will contribute towards 20% of your final grade. Everyone must make individual presentation of his own work, even
    in the case of group project.

    There are two deliverables in your report of the term project:

    A survey part that describes the problem domain, with proper problem definition, and a survey of existing work. This should be about 20 typed pages (12pt type with 1.5 spacing).

    A research part which will describe your own attempt to either solve the problem addressed in the survey part or go a long way towards its solution. What I minimally expect is a good solution approach such that if I gave you 2-3 more months, you could complete the solution, conduct the experiments and produce a publishable paper. This part should be about another 20 typed pages (12pt type with 1.5 spacing).

    Details of the submission of programming assignments will be written on each assignment handout. Students will be given a minimum of 3 weeks to work on each assignment. 

    Submissions of the term project will be made in hard copy and must be handed in in week 12.
    Course Grading

    Grades for your performance in this course will be awarded in accordance with the following scheme:

    M10 (Coursework Mark Scheme)
    Grade Mark Description
    FNS   Fail No Submission
    F 1-49 Fail
    P 50-64 Pass
    C 65-74 Credit
    D 75-84 Distinction
    HD 85-100 High Distinction
    CN   Continuing
    NFE   No Formal Examination
    RP   Result Pending

    Further details of the grades/results can be obtained from Examinations.

    Grade Descriptors are available which provide a general guide to the standard of work that is expected at each grade level. More information at Assessment for Coursework Programs.

    Final results for this course will be made available through Access Adelaide.

  • Student Feedback

    The University places a high priority on approaches to learning and teaching that enhance the student experience. Feedback is sought from students in a variety of ways including on-going engagement with staff, the use of online discussion boards and the use of Student Experience of Learning and Teaching (SELT) surveys as well as GOS surveys and Program reviews.

    SELTs are an important source of information to inform individual teaching practice, decisions about teaching duties, and course and program curriculum design. They enable the University to assess how effectively its learning environments and teaching practices facilitate student engagement and learning outcomes. Under the current SELT Policy ( course SELTs are mandated and must be conducted at the conclusion of each term/semester/trimester for every course offering. Feedback on issues raised through course SELT surveys is made available to enrolled students through various resources (e.g. MyUni). In addition aggregated course SELT data is available.

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  • Policies & Guidelines
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