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DTSTAMP:20260905T151158Z
DESCRIPTION:Click for Latest Location Information: http://edw2023fall.datav
 ersity.net/sessionPop.cfm?confid=157&proposalid=14629\nIn Pharma, large-sca
 le implementations FAIR principles (FAIR: findable, accessible, interoperab
 le, and reusable) have become a widely adopted strategy to drive the d
 igital transformation and to evolve into a data-driven industry. Howev
 er, until now, FAIR implementation excels in Research and Development. FAIR
  has not yet really made its way into Enterprise Data Management. In the pr
 esentation, we will give insights on our FAIR capability stack for referenc
 e data (terminology, metadata, schema definition, and conceptual models) an
 d its application in the Roche R&D data landscape to ensure semantic in
 teroperability.\n\nWe will also demonstrate how we apply FAIR to our Master
  Data by systematically providing global unique persistent, and resolvable 
 identifiers to our resources. The presentation will also explain the requir
 ed capabilities to build FAIR enterprise data and the governance of our ref
 erence data space at Roche. Finally, we expose our FAIR Architecture Playbo
 ok for IT Professionals.\n\n	FAIR applications, services, and data\n
 Information Architecture\n	Reference Data\n	Enterprise Data\n
 Data Governance\n\n
DTSTART:20230920T083000
SUMMARY:Linking FAIR Information Architecture with Enterprise Data
DTEND:20230920T091459
LOCATION: See Description
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