Introduction to e-Science
Overview
To develop a familiarity with a broad range of skills that are required to tackle the “big data†challenges of modern science-related careers. The subject introduces the fundamentals of e-Science and the key role that information technology plays in scientific discovery. This subject has a practical component, where students will build their skills in data analysis, visualization and programming.
Requisites
Learning outcomes
Students who successfully complete this unit will be able to:
- Select and use appropriate data analysis and visualization strategies
- Explain and apply the fundamentals of computer programming
- Explain the opportunities for, and challenges facing, scientific progress in the era of Data-Driven Science
- Apply e-Science strategies and approaches to science discipline-specific requirements
Teaching methods
Hawthorn
| Type | Hours per week | Number of weeks | Total (number of hours) |
|---|---|---|---|
| Face to Face Contact (Phasing out) Lecture | 2.00 | 12 weeks | 24 |
| Face to Face Contact (Phasing out) Laboratory | 1.00 | 10 weeks | 10 |
| Online Contact (Phasing out) Online Learning Activities | 0.67 | 12 weeks | 8 |
| Unspecified Learning Activities (Phasing out) Independent Learning | 9.00 | 12 weeks | 108 |
| TOTAL | 150 |
Sarawak
| Type | Hours per week | Number of weeks | Total (number of hours) |
|---|---|---|---|
| Face to Face Contact (Phasing out) Lecture | 2.00 | 12 weeks | 24 |
| Face to Face Contact (Phasing out) Laboratory | 2.00 | 12 weeks | 24 |
| Online Contact (Phasing out) Online Learning Activities | 0.67 | 12 weeks | 8 |
| Unspecified Learning Activities (Phasing out) Independent Learning | 7.83 | 12 weeks | 94 |
| TOTAL | 150 |
Assessment
| Type | Task | Weighting | ULO's |
|---|---|---|---|
| Assessment | Individual | 15 - 25% | 1,2,3,4 |
| Examination | Individual | 30 - 40% | 1,2,3,4 |
| Laboratory Report | Individual | 35 - 45% | 1,2,3,4 |
| Online Tests | Individual | 10 - 20% | 1,2,3,4 |
Hurdle
As the minimum requirements of assessment to pass a unit and meet all ULOs to a minimum standard, an undergraduate student must have achieved:
(i) an aggregate mark of 50% or more, and(ii) at least 40% in the final exam.Students who do not successfully achieve hurdle requirement (ii) will receive a maximum of 45% as the total mark for the unit.
Content
- Data-Driven Science and the evolution of the scientific method
- Characterising data (mean, standard deviation, quartiles, median, mode, histograms)
- Visualisation techniques and strategies – two-dimensional and three-dimensional data
- Data mining and knowledge discovery
- Information and communication technologies and methods for scientists
- Fundamentals of computer programming
- Algorithms, problem solving, and tools for scientists
- Emerging technologies for e-Science
- Big Data challenges and opportunities
- Current issues in e-Science (e.g. ethics, privacy, and security of data)
Study resources
Reading materials
A list of reading materials and/or required textbooks will be available in the Unit Outline on Canvas.