Virtual Observatory (P01342)

? Credit Points : 10 ? SCQF Level : 11 ? Acronym : PHY-P-VOB

This course introduces the Virtual Observatory (VObs) as a case study of the application of e-Science technologies to support research in a particular scientific domain, namely astronomy. It will cover the scientific motivation for the VObs from within astronomy, as well as the technical and sociological challenges in designing and building the VObs. The course will comprise lectures and practical exercises, which will familiarise students with the principles underlying the VObs, as well as giving them experience of using the tools which currently implement those ideas.

The course will assume no previous knowledge of astronomy, and so will be equally suitable for e-Science students interested in the VObs as an integrated e-Science application and astronomers wish to learn how to use it for their research. This course will be delivered by staff at the forefront of the development and use of the global Virtual Observatory.

Entry Requirements

? This course is not available to visting students.

? Pre-requisites : Only postgraduates or final year MPhys students with suitable computational background, subject to space restrictions and agreement with relevant Programme Coordinator.

Subject Areas

Home subject area

Postgraduate (School of Physics), (School of Physics, Schedule Q)

Delivery Information

? Normal year taken : Postgraduate

? Delivery Period : Semester 2 (Blocks 3-4)

? Contact Teaching Time : 2 hour(s) per week for 11 weeks

All of the following classes

Type	Day	Start	End	Area
Lecture	Monday	11:10	12:00	KB
Lecture	Monday	12:10	13:00	KB

Summary of Intended Learning Outcomes

On completion of this course, students should be able to:
1. Describe the scientific motivation for the Virtual Observatory (VObs)and the sociological challenges in creating it.
2. Demonstrate an understanding of the VObs architecture and of the technical choices made in its design.
3. Describe the function of the major components of the VObs.
4. Use a range of existing VObs tools to run well-defined scientific analyses.
5. Prepare a pre-existing dataset for publication in the VObs.
6. Prepare a pre-existing data analysis tool for deployment in the VObs.
7. Critique the standards and protocols that provide the basis of the VObs.