Search

Start Over Subject distributed-computing Resource Type Education Content Level Amateur
1. A Short Course On PyVO
ID:
ivo://org.gavo.dc/tutreg/gavo_pyvocourse/rec
Title:
A Short Course On PyVO
Short Name:
GAVO pyvo course
Date:
27 Dec 2024 08:31:13
Publisher:
The GAVO DC team
Description:
This is a course on pyVO, an astropy-affiliated Python library implementing client parts for many protocols in the Virtual Observatory: Simple discovery protocols like SCS, SIAP, and SSAP as well as the sophisticated Table Access Protocol TAP, which allows users to send complex queries to remote tables and retrieve metadata-rich results. There is also an interface to the VO Registry to enable data and service discovery. The course comes with many exercises, most of which also have solutions. We hope it is suitable for both self-study and as lecture notes in teacher-led situations.
2. Using the Virtual Observatory
ID:
ivo://org.gavo.dc/tutreg/gavo_vocourse/rec
Title:
Using the Virtual Observatory
Short Name:
GAVO vo course
Date:
27 Dec 2024 08:31:06
Publisher:
The GAVO DC team
Description:
This is a course on using the Virtual Observatory (VO), an international research data infrastructure in Astronomy and Astrophysics. Starting with a brief discussion of some general concepts, it introduces some of the major client programs like TOPCAT and Aladin, together with some simple discovery protocols. A first focus topic is the query language ADQL, which is treated within the equivalent of three lectures. The second major focus of the course is the premier Python interface to the VO, pyVO, which is used to also more deeply investigate the topics treated before. The course is complemented by a number of side tracks, brief discussions of more fundamental or more specialised VO topics. The course comes with many exercises, most of which also have solutions. We hope it is suitable for both self-study and as lecture notes in teacher-led situations. In the latter case, it is designed to work as a semester-long course with two hours of lectures and lab work each per week.