This brief tutorial shows you how to quickly add proper motions and
photometry from Gaia to (almost) any object list using the Virtual
Observatory. The VO protocol most suited to this kind of this is TAP
("table access protocol") and lets you transfer data and queries to
database servers. In the example, we will be using TOPCAT as a client.
There is no lock-in to it: There are libraries and other tools
allowing an integration of TAP operations into arbitrary workflows –
that's what standards are about. Tutorial supplements apply the
techniques to Simbad, show how to use TAP from Python, and introduce
UCDs.
This course introduces advanced usage of Hierarchical Progressive
Surveys (HiPS) and Multi-Order Coverage (MOC) maps in Aladin. Using
this document, you will learn how to handle a problem like : “I have a
set of images. I would like to select regions in my observations that
are above a given threshold in another survey (e.g. at low
extinction), retrieve objects from very large catalogs (e.g. Gaia +
WISE) in these non-trivial shapes and not-necessarily-connected
regions, and combine them to visualise some quantities (e.g. color
color diagram).“
This tutorial shows how to use the CDS tools to gather information on
specific astronomical objects. The tutorial covers the search for
information on NGC 4039 in the CDS Portal, the search for data on NGC
4039 in Aladin, and the omparison of the coverages of Sky Surveys and
select interacting galaxies that have SDSS and GALEX data.
This is a course on the Virtual Observatory's main query language
ADQL (short for Astronomical Data Query Language), which is a SQL
dialect standardised so users do not have to learn new languages each
time they want to use a new resource. We also introduce the basic
aspects of the Table Access Protocol TAP, which transports ADQL
queries, their results as well as the metadata necessary to write
meaningful queries.
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.
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.
In this tutorial you will learn about asteroids, a very interesting
and current topic in our exploration of the Solar System and of
planetary formation. You will learn about their orbital
characteristics by querying a database.
Intermediate computer skills are recommended, as the tutorial requires
the (guided) query of online electronic databases and use of
histograms.
The VO client Aladin offers powerful facilities of creating an
astrometrical calibration to images lacking WCS (World Coordinate
System) information. This tutorial shows how to go about doing this
for an image of the Ring Nebula in Lyr.
The overall goal of this tutorial is to become familiar with VOSpec.
For that, we are going to build the Spectral Energy Distribution (SED)
of two Herbig Ae/Be stars, compare them and categorise them as group 1
or group 2 Herbig Ae/Be stars.
This tutorial uses SPLAT-VO to search the VO registry for spectra of
galaxies and quasars. From the obtained spectra, the Hydrogen Lyman
Alpha line will be used to compute redshift and velocity
Within this intermediate use case you learn about supernovae (see
also the tutorial “Distance to the Crab Nebula“,
ivo://edu.euro-vo.org/tutorials/08_m1_distance) and determine the
celestial coordinates of a just discovered candidate supernova on an
provided image without astrometric calibration. This use case provides
a glimpse of an activity that is representative of the practical tasks
that astronomers have to perform when they analyze data.
![To the extent possible under law, the publisher has waived all copyright and related or neighboring rights to GAVO's ADQL course. For details, see the `Creative Commons CC0 1.0 Public Domain dedication <http://creativecommons.org/publicdomain/zero/1.0/>`_. Of course, you should still give proper credit when using this data as required by good scientific practice. .. image:: /static/img/cc0.png :alt: [CC0]](/registry-search/?f%5Brights_facet%5D%5B%5D=To+the+extent+possible+under+law%2C+the+publisher+has+waived+all+copyright+and+related+or+neighboring+rights+to+GAVO%27s+ADQL+course.++For+details%2C+see+the+%60Creative+Commons+CC0+1.0+Public+Domain+dedication+%3Chttp%3A%2F%2Fcreativecommons.org%2Fpublicdomain%2Fzero%2F1.0%2F%3E%60_.++Of+course%2C+you+should+still+give+proper+credit+when+using+this+data+as+required+by+good+scientific+practice.%0A%0A..+image%3A%3A+%2Fstatic%2Fimg%2Fcc0.png%0A+++%3Aalt%3A+%5BCC0%5D%0A%0A&f%5Bsubject_facet_lc%5D%5B%5D=software-tutorials&f%5BvalidationLevel_facet%5D%5B%5D=2){kind=link}