We are pleased to announce our Tutorial RDM4AI on Research Data Management in Data Science and AI - Avoiding a Replicability Crisis co-located with KI 2024.
This tutorial addresses the replicability crisis in Artificial Intelligence, with a particular focus on machine-based learning approaches. It covers the research data life cycle, emphasizing best practices for data/software management, metadata, documentation, versioning, and sharing practical examples on how to achieve such practices. Additionally, it introduces model and dataset cards for comprehensive reporting, and advocates for the adoption of FAIR Data Principles to transform research outputs into FAIR Data Objects (FDOs). Aimed at academics across all domains working on AI fields, the tutorial provides practical guidance to enhance transparency and accountability, fostering a more reliable and impactful AI landscape.
RDM4AI Hands-On Sessions:
- Model and dataset cards
- Adopting the FAIR Data Principles (Findable, Accessible, Interoperable, and Reusable)
- RO-Crate + Sign Posting to create FDOs
More information: https://sites.google.com/view/rdm4ai-2024/.