A recent publication may be relevant for expanding the section on the methodological foundations and lifecycle perspective of Data-centric AI:
A recent publication may be relevant for expanding the section on the methodological foundations and lifecycle perspective of Data-centric AI:
Malerba, D., Poggi, A., Alviano, M., et al. “Data-Centric AI Manifesto: How Data Quality Drives Modern AI”, Electronics 15(9), 1913 (2026). https://doi.org/10.3390/electronics15091913
The paper discusses Data-centric AI as a methodological paradigm distinct from traditional model-centric AI approaches and proposes:
The article may be relevant as a recent perspective on how DCAI is evolving toward broader concerns including data governance, semantic consistency, lifecycle management, and robustness of generative models.
This paper represents a key outcome of the Transversal Project TP7 "Data-Centric AI and Infrastructures", part of the FAIR - Future Artificial Intelligence Research extended partnership (PNRR, Italy), which is now coming to its conclusion. FAIR has been a truly cross-community effort, involving almost the entire Italian AI research landscape. ~2026-29756-63 (talk) 11:22, 18 May 2026 (UTC)
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