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DESCRIPTION:Click for Latest Location Information: http://edw2018.dataversi
 ty.net/sessionPop.cfm?confid=121&proposalid=9669\n<p>Ontologies are models 
 that capture meaning in a machine-readable form. If I told you my parents h
 ad three boys, Jim, Daniel, and me, you would know Jim and Daniel were my b
 rothers, even though I didn&rsquo;t tell you that. With an ontology, you ca
 n easily define family relationships, so the computer can infer the unstate
 d fact they are my brothers just like you, a human, can. A traditional data
  structure would require several joins. A graph database stores the schema 
 and data together, pre-joined in packets called triples, i.e. George isPare
 ntOf Mark, Mary isParentOf Jim. The graph database can then be directly que
 ried (with SPARQL) to retrieve the stated and infer the unstated data. But 
 here&rsquo;s the thing: the ontology creates the mathematical precision to 
 know, not just guess, at the unknown. This IS the next disruptive technolog
 y, and you should invest the time to at least understand it!</p>\n\n
 Ontologies model meaning with mathematical precision\n
 Graph databases pre-join data under management\n
 Ontology-driven data management can accurately infer data that isn&rsquo;t 
 even there\n
 Data can be integrated in place by its meaning rather than table and column
  names\n\n<p>Come find out how ontology-driven systems will replace our cur
 rent brittle environments.</p>\n
DTSTART:20180426T081500
SUMMARY:Why I Ignored Ontology and Graph DB, and Why You Shouldn't
DTEND:20180426T091459
LOCATION: See Description
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