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...

This tutorial will show how tabular data can be easily transferred from Topcat to Aladin or the other way, and it will illustrate the benefits of this inter-client communication for VO users. This is shown with a quick look at filtering members of the Coma Cluster from SDSS.

Low-resolution spectra like those resulting from objective prism observations or the RP/BP instrument on board of the Gaia astrometry satellite enable a wealth of interesting science. This use case investigates one use leading up to combining many VO resources: The identification of misclassified objects from reference databases.

As stars in open star clusters are formed from the same matter at the same time and have only a small velocity dispersion, it is relatively easy to identify them from the background stars. In this tutorial, we will identify the members of the Pleiades kinematically and get an idea of our success by examining a color-magnitude diagram using TOPCAT, Aladin, and a few VO services.

This tutorial introduces a few techniques for working with image services in the Virtual Observatory (VO) in general, using services containing plate scans as examples. It will discuss both exploratory, interactive use, and scripting using pyVO.