Postgraduate Course: Fundamentals of Data Management (EPCC11005)
Course Outline
| School | School of Informatics |
College | College of Science and Engineering |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Availability | Available to all students |
| SCQF Credits | 10 |
ECTS Credits | 5 |
| Summary | Better and more effective approaches to managing digital research data are becoming increasingly important in computational science and beyond. The scientific data sets that underpin research papers can now occupy many gigabytes of storage, and are increasingly complex and challenging to work with. This course introduces students to the ideas, methods and techniques of modern, digital data management. |
| Course description |
The course will cover:
- Why managing research data better matters, and why it's hard
- Data management planning: a required part of twenty first century research
- Data formats: structuring data and keeping them useful
- Relational and NoSQL databases
- Metadata: describing data and keeping them useful
- Publication and citation of research data
- Persistence, preservation and provenance of research data
- Licensing, copyright and access rights: some things researchers need to know
- Important distributed data processing tools and techniques, such as: Spark and MapReduce
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
|
Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
Information for Visiting Students
| Pre-requisites | None |
| High Demand Course? |
Yes |
Course Delivery Information
|
| Academic year 2023/24, Available to all students (SV1)
|
Quota: 84 |
| Course Start |
Semester 1 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
100
(
Lecture Hours 22,
Supervised Practical/Workshop/Studio Hours 11,
Summative Assessment Hours 2,
Revision Session Hours 1,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
62 )
|
| Assessment (Further Info) |
Written Exam
70 %,
Coursework
30 %,
Practical Exam
0 %
|
| Additional Information (Assessment) |
Written Exam 70%
Coursework (Assessed practicals) 30%
Written examination comprised of 3 compulsory questions (equally weighted).
The coursework elements are comprised of assessed practicals spread throughout the Semester. These will be short quizzes taken following practical classes with each worth 10%. |
| Feedback |
Provided via practical class sessions, assessed practicals, and after the exam. |
| Exam Information |
| Exam Diet |
Paper Name |
Hours & Minutes |
|
| Main Exam Diet S1 (December) | Fundamentals of Data Management | 2:00 | |
Learning Outcomes
On completion of this course, the student will be able to:
- Identify common data formats and understand applicable usage of these.
- Demonstrate both an understanding of data storage techniques and an ability to apply these techniques
- Explain and appreciate the importance of long-term data management
- Analyse important distributed data processing models
- Synthesise these concepts to address data management problems
|
Reading List
| Made available via Learn/Leganto |
Additional Information
| Graduate Attributes and Skills |
- Solution Exploration, Evaluation and Prioritisation.
- Critical thinking
- Communication of complex ideas in accessible language
- Working in an interdisciplinary field
- Programming and Scripting |
| Special Arrangements |
There are limited spaces on this course. |
| Keywords | FDM,EPCC,Data Science,Data Management,Data Processing,Databases,NoSQL,HPCwDS,MapReduce,Spark,Data |
Contacts
| Course organiser | Dr Christopher Wood
Tel: (0131 6)51 5330
Email: C.Wood@epcc.ed.ac.uk |
Course secretary | Mr James Richards
Tel: 90131 6)51 3578
Email: J.Richards@epcc.ed.ac.uk |
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