FAIR Re-use: Implications for AI-Readiness

dc.creatorFletcher, Lydia
dc.date.accessioned2024-04-18T22:24:01Z
dc.date.available2024-04-18T22:24:01Z
dc.date.issued2024-04-16
dc.description.abstractA discussion of how to use the FAIR data principles to ensure quality data is being used in machine learning models. Presented at AI-Ready Data: Navigating the Dynamic Frontier of Metadata and Ontologies April 15-16, 2024
dc.description.departmentTexas Advanced Computing Center (TACC)
dc.identifier.urihttps://hdl.handle.net/2152/124873
dc.identifier.urihttps://doi.org/10.26153/tsw/51475
dc.relation.ispartofUT Faculty/Researcher Worksen
dc.rightsAttribution-NonCommercial-ShareAlike 3.0 United Statesen
dc.rights.restrictionOpen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/us/
dc.subjectFAIR data
dc.subjectdata management
dc.subjectmachine learning
dc.titleFAIR Re-use: Implications for AI-Readiness
dc.typePresentation

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