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DESCRIPTION:Click for Latest Location Information: http://edw2011.wilshireconferences.com/sessionPop.cfm?confid=52&proposalid=3759\nPART 1: \nOn a global scale, the Semantic Web promises a linked web of data.  The same technology can be used on an enterprise scale to integrate data.  But the realities of using Semantic Web standards for Enterprise Data Integration can be daunting, even to someone familiar with them. This tutorial explains how the simplicity of the RDF data model allows it to act as an interlingua between other linked data representations, providing a simple, unified paradigm for data integration.  Information from any source format is translated into RDF in an information-preserving manner, without regard to specifics of its content.  The resulting RDF is then merged with that of other data sources.  Content-specific mappings are accomplished with SPARQL CONSTRUCT queries to identify patterns in the source data. \nThe tutorial will review the basics of RDF and SPARQL, emphasizing the features that make them particularly suitable for enterprise data integration.  The bulk of the session will focus on data integration itself, including the following topics: \n<ul><li>Semantic Enterprise Data Integration lifecycle</li>\n<li>RDF basics, and why RDF is a good representation for integrating data</li>\n<li>The role of the URI in sharing data </li>\n<li>How RDF relates to familiar data representations: spreadsheets, XML, databases, email, etc. </li>\n<li>RDF and unstructured data</li>\n<li>SPARQL as a means for linking information</li>\n<li>Querying the integrated data</li></ul>\nPART 2:\nA Semantically-enabled Enterprise Database Management System marries the rich information discovery and data integration of semantic technologies with the mature, enterprise features of a commercial RDBMS.  Applications in defense and intelligence, life sciences and clinical medicine, finance, publishing, and entertainment have RDF graphs running to tens of billions of triples, usually with associated relational, XML, text and/or spatial data. These applications require RDBMS-strength scalability, querying and security features with persistent beyond memory-scale inferencing. Learn how Oracle Database Semantic technologies  has implemented scalable RDF storage, querying, and native inferencing that conforms with W3C standards and open source frameworks: RDF, RDFS, OWL 2, SPARQL, SKOS, Jena and Sesame, and SQL integration.
DTSTART:20110404T083000
SUMMARY:T9: Semantic Technologies and Linked Data for Enterprise Data Management
DTEND:20110404T164459
LOCATION: See Description
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