AutoData Steward: An AI-Driven Framework for FAIR-Compliant Data Lifecycle Optimization in HPC Environments (Conference Abstract)

This record contains the accepted conference abstract of the work titled: "AutoData Steward: An AI-Driven Framework for FAIR-Compliant Data Lifecycle Optimization in HPC Environments." The proposed framework introduces an AI-driven approach for intelligent data lifecycle management in High Performance Computing (HPC) environments. It integrates FAIR data principles (Findable, Accessible, Interoperable, Reusable) with automated metadata enrichment, machine learning-based storage optimization, and policy-driven lifecycle control mechanisms. The system aims to improve storage efficiency, enhance research data discoverability, and support sustainable data stewardship in large-scale computing infrastructures. This record includes the officially published one-page abstract as it appeared in the NHR Conference 2026 Book of Abstracts. Keywords: Artificial Intelligence, FAIR Data, High Performance Computing, Data Lifecycle Management, Research Data Management, Storage Optimization.