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DESCRIPTION:Click for Latest Location Information: http://dgiq-aigov2026.da
 taversity.net/sessionPop.cfm?confid=166&proposalid=16811\nAs biomedical res
 earch scales, balancing open science with robust data protection has become
  a critical bottleneck. Traditional data governance models, built for an er
 a of manual compliance and localized computing, are increasingly incompatib
 le with modern cloud-based ecosystems. Drawing on lessons from the NHGRI An
 VIL ecosystem—which manages over 10 PB of sensitive genomic and 
 clinical data—this session explores the operational realities of mode
 rnizing data access. We will address the friction point of applying outdate
 d governance frameworks to cloud-based systems and advanced computatio
 nal tools like Large Language Models (LLMs). By examining strategies employ
 ed and evolving in the AnVIL, this talk highlights how technical standards 
 and scalable policies can co-exist with increasingly complex data infrastru
 cture, without impeding progress. Attendees will gain actionable insights i
 nto navigating current institutional compliance challenges while building t
 he flexible, secure data sharing infrastructure required for the future of 
 AI-driven discovery.\nKey Takeaways & Learning Objectives:\n\n	\n
 Scaling Governance to Petabyte Ecosystems: Lessons learned from managi
 ng, securing, and sharing over 10 PB of diverse NIH data within the cl
 oud-based AnVIL platform.\n	\n	\n
 Modern Machines vs. Legacy Rules: Navigating the regulatory and ethica
 l friction of deploying Large Language Models (LLMs) and automated workflow
 s on controlled-access datasets.\n	\n	\n
 Automating Compliance with the Data Use Ontology: How leveraging the D
 ata Use Ontology to translate complex, consent-based legal requirement
 s can lead to scalable, automated access decisions.\n	\n	\n
 Overcoming Institutional Bottlenecks: Practical strategies for shiftin
 g research institutions away from manual, siloed data-sharing agreements to
 ward federated, secure ecosystems with facilitated data access agreement co
 ntracting.\n	\n	\n
 Opportunities for Future Standards: A look ahead at how global policy 
 frameworks (e.g., GA4GH) are evolving to advance both data democratization 
 and data security simultaneously.\n	\n\n
DTSTART:20261117T134500
SUMMARY:Advancing Data Sharing and Security Simultaneously - Lessons Learne
 d, Challenges, and Opportunities
DTEND:20261117T142959
LOCATION: See Description
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