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DESCRIPTION:Click for Latest Location Information: http://das2018.dataversi
 ty.net/sessionPop.cfm?confid=124&proposalid=9985\n<p>Semantics are already 
 disrupting the data management status quo and for very good reasons. Ontolo
 gies define data dramatically more effectively than traditional ER modeling
  ever could, and they can be directly executed without translation from con
 ceptual to logical to physical. This session will leverage existing open st
 andards such as OWL, SPARQL, R2RML, Data Centric, etc., to present a comple
 te solution in the following three steps:</p>\n<ol>\n
 Define, not describe, the subject data in sufficient detail to identify the
  data set. This is done by creating an ontology. The difference between def
 ining (semantics) and describing (relational) will be clarified as well.\n
 Create mappings between the ontology and your existing data. This is a dire
 ct mapping, using the ontology, to any data source that contains the data d
 efined in the ontology.\n
 Execute the mappings to either move the data into a graphDB, or virtualize 
 data access without moving it out of existing systems.\n</ol>\n<p><br />\nT
 his presentation is tailored for data professionals that, like me, have ign
 ored or even been intimidated by ontologies and graph databases. This is an
  approach and a collection of technologies that have often been presented a
 s only available to a high priesthood of specialized talent, and it just do
 esn&rsquo;t have to be that way. While it is true that there is complexity,
  for what branch of information management is that not true?</p>\n
DTSTART:20181010T154500
SUMMARY:RDBMS to GraphDB in Three Steps
DTEND:20181010T164459
LOCATION: See Description
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