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COMP9036 - Databases & Ontologies

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Title:Databases & Ontologies
Long Title:Databases & Ontologies
Module Code:COMP9036
 
Credits: 10
NFQ Level:Expert
Field of Study: Computer Science
Valid From: Semester 1 - 2014/15 ( September 2014 )
Module Delivered in 2 programme(s)
Module Coordinator: TIM HORGAN
Module Author: BYRON TREACY
Module Description: Databases, knowledge bases, ontologies are a means of acquisition and representation of essential empirical and conceptual knowledge and are essential tools in Computational Biology. Hence there is a demand for practitioners who have attained expert knowledge, skill and competence in the theory and practice of data and knowledge management. Knowledge bases and ontologies that store relevant data must be designed and structured to maximise the generation and exchange of relevant and usable information.
Learning Outcomes
On successful completion of this module the learner will be able to:
LO1 Explain terms and concepts relating to the storage and processing of data in computer systems.
LO2 Apply data modelling constructs in the biological/biomedical domain.
LO3 Apply data retrieval constructs in the biological/biomedical domain.
LO4 Explain terms and concepts of distributed data, particularity the application of the Semantic Web in computational biology.
Pre-requisite learning
Module Recommendations
This is prior learning (or a practical skill) that is strongly recommended before enrolment in this module. You may enrol in this module if you have not acquired the recommended learning but you will have considerable difficulty in passing (i.e. achieving the learning outcomes of) the module. While the prior learning is expressed as named CIT module(s) it also allows for learning (in another module or modules) which is equivalent to the learning specified in the named module(s).
No recommendations listed
Incompatible Modules
These are modules which have learning outcomes that are too similar to the learning outcomes of this module. You may not earn additional credit for the same learning and therefore you may not enrol in this module if you have successfully completed any modules in the incompatible list.
No incompatible modules listed
Co-requisite Modules
No Co-requisite modules listed
Requirements
This is prior learning (or a practical skill) that is mandatory before enrolment in this module is allowed. You may not enrol on this module if you have not acquired the learning specified in this section.
No requirements listed
Co-requisites
No Co Requisites listed
 

Module Content & Assessment

Indicative Content
Introduction to key concepts in computer data storage and processing
Computing terms & concepts relating to data and data processing. Biological data from an I.T. perspective. Integration.
Building Data models and Knowledge Bases
Data/System modelling, Schemas, Normalisation, Resource description Frameworks, XML, Bioinformatics Ontologies
Retrieving Knowledge
Information Retrieval, Sequence Similarity Searching Tools, Query Languages, Inference.
Distributed Data & the Semantic Web
Semantic web technologies e.g. Ontology languages (OWL), The Semantic Web and Bioinformatics Applications, Survey of Ontologies in Bioinformatics.
Assessment Breakdown%
Course Work30.00%
End of Module Formal Examination70.00%
Course Work
Assessment Type Assessment Description Outcome addressed % of total Assessment Date
Short Answer Questions A written assessment based on material covered in class notes, practical work and project based research. 1,2,3,4 30.0 Week 9
End of Module Formal Examination
Assessment Type Assessment Description Outcome addressed % of total Assessment Date
Formal Exam End-of-Semester Final Examination 1,2,3,4 70.0 End-of-Semester
Reassessment Requirement
Repeat examination
Reassessment of this module will consist of a repeat examination. It is possible that there will also be a requirement to be reassessed in a coursework element.

The institute reserves the right to alter the nature and timings of assessment

 

Module Workload

Workload: Full Time
Workload Type Workload Description Hours Frequency Average Weekly Learner Workload
Lecture Lecture 4.0 Every Week 4.00
Lab Lab 2.0 Every Week 2.00
Independent & Directed Learning (Non-contact) No Description 8.0 Every Week 8.00
Total Hours 14.00
Total Weekly Learner Workload 14.00
Total Weekly Contact Hours 6.00
This module has no Part Time workload.
 

Module Resources

Recommended Book Resources
  • Dean Allemang, James Hendler, Semantic web for the working ontologist [ISBN: 0123735564]
  • Kenneth Baclawski and Tianhua Niu 2005, Ontologies for Bioinformatics, MIT Press [ISBN: ISBN-10:0-262-02591-4]
  • Elmasri & Navathe 2011, Database Systems, 6th Ed., Pearson [ISBN: 13: 978-0-13-214498-8]
  • Connolly & Begg 2014, Database Systems, 6th Ed., Pearson [ISBN: 9780132943260]
Supplementary Book Resources
  • 2010, Bioinformatics Databases: Design, Implementation, and Usage, CRC [ISBN: ISBN-10: 1584884975]
This module does not have any article/paper resources
Other Resources
 

Module Delivered in

Programme Code Programme Semester Delivery
CR_SCMPB_9 Masters of Science in Computational Biology 1 Mandatory
CR_SCMBI_9 Postgraduate Diploma in Computational Biology 1 Mandatory

Cork Institute of Technology
Rossa Avenue, Bishopstown, Cork

Tel: 021-4326100     Fax: 021-4545343
Email: help@cit.edu.ie