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DESCRIPTION:Click for Latest Location Information: http://semtechbizsf2012.semanticweb.com/sessionPop.cfm?confid=65&proposalid=4696\nRDF is the ultimate data mashup language--it's a straightforward task to convert data from all the most common enterprise formats (spreadsheets, XML, relational databases) into RDF. RDF provides a simple and standards-based way to merge this data into a single, queryable dataset. While this works well in principle, and even in practice at small scale, this well-known approach faces specific challenges when applied to large scale information sets. We'll look at a small-scale, dynamic approach that that lets users navigate over large amounts of federated data. The trick to the approach is to access large scale data while storing only a small, manageable amount of data at any one time. While this approach is not a data integration silver bullet, it does make it easier to dynamically explore large collections of heterogeneous data, letting you find new connections that may not have been apparent before.\n? RDF and the promise of data mashups\n? Defintion: Dynamic Data Federation\n? Application areas: Pharmaceuticals, National Intelligence, Investment Banking, etc.\n? Strenghts and Weaknesses of Dynamic Data Federation\n? Comparison to other data federation approaches
DTSTART:20120607T104500
SUMMARY:Dynamic Data Federation: When and How it Really Works
DTEND:20120607T112959
LOCATION: See Description
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