Towards Enhancing WaaS and Data Provenance over Reana: Enhancing Reproducibility on the European AI-on-Demand Platform

Presenter: Antonis Ganios (NCSR “Demokritos”)
Co-Authors: Iraklis Klampanos, Antonis Troumpoukis

Schedule: Session 3 (Amsterdam / Online hybrid) Wednesday 15 May, APAC-EMEA Friendly time

Summary: REANA is a data analysis platform developed by CERN that enhances scientific reproducibility by enabling researchers to describe, execute, and share analyses using standardised workflows such as CWL in reusable containers, deployable across Cloud and HPC resources. We are enhancing REANA’s functionality by enabling users to register, execute, and monitor CWL workflows. We are implementing a data provenance capture mechanism for based on the W3C PROV-O standard. Using dynamic placeholders in CWL syntax, our platform emphasises integration with a catalogue of assets, such as AI models, datasets and resources, in order to enable reuse and reproducibility, and encourage scientific collaborations and the sharing of existing resources amongst researchers. Our provenance system for REANA will be made available as part of the European AI-on-Demand platform to meet the needs of AI innovators and researchers for large-scale workflows.

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