AAS 207th Meeting, 8-12 January 2006
Session 25 VO and Source Surveys
Poster, Monday, 9:20am-7:00pm, January 9, 2006, Exhibit Hall

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[25.01] Knowledge Discovery Framework for the Virtual Observatory

B. Thomas, E. Shaya, Z. Huang, P. Teuben (UMD)

In this poster 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. In this poster, we will present UML diagrams of the overall framework and, using an example use-case, will show how the scientist will interact with the framework using a science based terminology rather than a datacentric one.

If you would like more information about this abstract, please follow the link to http://archive.astro.umd.edu/VOFramework. This link was provided by the author. When you follow it, you will leave the Web site for this meeting; to return, you should use the Back comand on your browser.

The author(s) of this abstract have provided an email address for comments about the abstract: thomas@astro.umd.edu

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