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Follow up on our conference call on 7/11...

From: Ezzat, Ahmed <Ahmed.Ezzat@hp.com>
Date: Thu, 17 Jul 2008 01:05:31 +0000
To: "public-xg-rdb2rdf@w3.org" <public-xg-rdb2rdf@w3.org>
Message-ID: <3B7AE9BA67C72B4891EF21842246A21C3585138741@GVW1097EXB.americas.hpqcorp.net>

Hello,

This is a question that I would be interested in hearing your reaction and views about.

In a multiple data sources environment where some of them are huge like data warehouses, it seems like transforming all data sources into RDF then querying that RDF store using SPARQL is going to put too much pressure on the RDF store beyond reasonable.  In addition all changes in these data sources need to be reflected in the RDF store as soon as possible.  In the above paragraph I am ignoring the notion of local and domain Ontologies.

An alternative I am exploring is to decompose the user query into set of subqueries (SQL and Search) operations to the relevant data sources (i.e., context) --> transform the results into RDF using local Ontologies then resolve differences using the domain ontology --> apply the SPARQL query on the union of the RDF graphs after reconciliation.   Even this approach is far better from RDF storage point of view (i.e., scalability), it seems like response time can be less than desirable?

Comments and thoughts including additional alternatives...
Regards,

Ahmed



Ahmed K. Ezzat, Ph.D.
HP Fellow, Business Intelligence Software Division
Hewlett-Packard Corporation
19333 Vallco Parkway, MS 4502, Cupertino, CA 95014-2599
Office:      Email: Ahmed.Ezzat@hp.com<mailto:Ahmed.Ezzat@hp.com> Tel: 408-285-6022 Fax: 408-285-1430
Personal: Email: AhmedEzzat@aol.com<mailto:AhmedEzzat@aol.com> Tel: 408-253-5062 Fax: 408-253-6271







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Received on Thursday, 17 July 2008 01:07:24 GMT

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