Data-Centric AI Manifesto: How Data Quality Drives Modern AI
Abstract
This white paper represents the joint outcome of five partners within the FAIR project, spanning four different spokes, who collectively contributed to the activities of Transversal Project 7 (FAIR TP7 – Data-Centric AI and Infrastructures). The contributing institutions are: University of Bari Aldo Moro (Spoke 6), University of Calabria (Spoke 9), University of Naples Federico II (Spoke 3), University Sapienza of Rome (Spoke 5), and INFN – National Institute of Nuclear Physics (Spoke 6). Their coordinated effort reflects the interdisciplinary and multi-institutional nature of FAIR, reinforcing the central role of data-centric methodologies in advancing trustworthy and robust AI systems.
Fields of Study & Subjects
Data Quality and Management
Ethics and Social Impacts of AI
Machine Learning and Data Classification
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 15 January 2026
- Language
- EN