Postgraduate Course: Case Studies in Analytical and Scientific Databases (INFR11018)
|School||School of Informatics
||College||College of Science and Engineering
||Availability||Available to all students
|Credit level (Normal year taken)||SCQF Level 11 (Postgraduate)
|Home subject area||Informatics
||Other subject area||None
||Taught in Gaelic?||No
|Course description||This course has been designed to introduce students to real examples of research in the field of Scientific and Analytical Databases. A key component of the course will be the detailed evaluation and rational behind several current research projects that highlight the limitations of the ?state of the art= or novel use of the latest theories and technologies. The primary learning outcome is the development of specialist critical evaluation skills that can then be applied to future industrial application or academic research into advanced Database technology and problems.
Entry Requirements (not applicable to Visiting Students)
|| Students MUST have passed:
Applied Databases (INFR11015) AND
Querying and Storing XML (INFR10017)
||Other requirements|| For Informatics PG and final year MInf students only, or by special permission of the School.
|Additional Costs|| None
Information for Visiting Students
|Displayed in Visiting Students Prospectus?||No
Course Delivery Information
|Not being delivered|
Summary of Intended Learning Outcomes
|1 - Discuss the descision making and research processes behind current database research programmes.
2 - Describe the analytical methods applied to data and schema in scientific and commercial database systems
3 - Describe with examples, the practical limits of DBMS technology and theory
4 - Analyse and discuss real examples of DBMS structures
5 - Describe the development and life-cycle of DBMSs
6 - Discuss in groups DBMS problems and suggest potential solutions
7 - Critically evaluate research literature in the field
|Written Examination 40|
Assessed Assignments 60
Oral Presentations 0
The questions submitted each week for the group discussion session will be graded by the course staff. This will contribute 30% of the course mark. A further 30% will be a short dissertation (3000 words) describing an appropriate database not covered in the course. The final 40% will come from the end of term exam.
If delivered in semester 1, this course will have an option for semester 1 only visiting undergraduate students, providing assessment prior to the end of the calendar year.
Each week, a local or invited database research group will present the status of their project, along with the main aims and objectives. In advance of this presentation, the research group will post a link to research papers or articles describing their database or relevant database topics. At the start of the session, Students will submit three questions based on their interpretation of the literature supplied. These questions should be designed to clarify the research strategies or highlight alternative approaches for consideration.
After the initial presentation there will be a short coffee break followed by small group discussions on the presentations. At these discussions, all questions will be put on the table and their relevance discussed. Each group will be asked to select the best questions in light of the presentation for a panel to put to the researchers for discussion. The final session will take the form of an expert panel that will chair a discussion of the questions raised during the group sessions.
The core aims of this course mean that the examples used on an annual basis will have to be re-assed for current relevancy. Moreover, the selection of topics will be balanced to include a variety of perspectives that will include:
* Novel application of database theory or technology to unusual data structures
* Failures or limitations in current theory and/or technology
* Emergent database theories and their potential application to existing problems
* The analysis of large and complex database systems
* Contrasting the application of database science in commercial and academic sectors
Some examples of possible topics include:
Amazon Data mining.
Financial Database Analysis.
MRC Mouse Atlas and Database $ú 3D Volumetric DB models.
The Virtual Observatory.
FlyBase - integrating genomic and functional data.
Swissprot - provenance in curated Databases.
Axiope and NeuroML $ú Commercial and Academic DB development.
PPID (Genes2Cognition) $ú Text mining and database curation.
Relevant QAA Computing Curriculum Sections: Databases, Middleware, Developing Technologies, Information Retrieval, Information Retrieval, Web-based Computing
||Each week students will be asked to read one or more papers, as described in the "delivery" section. The list will vary from year to year.
||Study Format Hours
Timetabled Laboratories 0
Non-timetabled assessed assignments 30
Private Study/Other 50
|Course organiser||Dr Michael Rovatsos
Tel: (0131 6)51 3263
|Course secretary||Miss Gillian Bell
Tel: (0131 6)50 2692