Knowledge Discovery Framework for the Virtual Observatory
B. Thomas, E. Shaya, Z. Huang, P. Teuben (UMD) 

We describe a framework that allows a scientist-user to easily query for
information across all Virtual Observatory (VO) repositories and pull it back
for analysis. This framework hides the gory details of meta-data remediation
and data formatting from the user, allowing them to get on with search,
retrieval and analysis of VO data as if they were drawn from a single source.
Using an example use-case, will show how the scientist may interact with the
framework using a science based terminology rather than a data-centric one and
then we will describe critical components and considerations of the overall
framework which make use of Java-based technologies (Jena/Pellet) and W3C
standards (XML/OWL).