Fueling Industrial AI with Data Pipelines
The objective of the session, co-organised by the DataCloud, enRichMyData and Graph-Massivizer projects, is to create a forum for research and industry to discuss challenges and opportunities in the emerging field of Big Data pipelines operating under the Computing Continuum paradigm, with applicability to Industrial AI applications. The session will highlight a set of different digital technologies and methods, which offer new solutions for the always more complex field of operation of heterogeneous and big data pipeline systems with applicability to industrial AI applications.
This session will discuss the main trends in the ongoing data-driven AI, the Cloud/Edge/Fog Computing Continuum and its significance for the future processing of big data for industrial AI systems. The Computing Continuum – federating Cloud services with emerging Edge and Fog computing paradigms –enables new opportunities for supporting Big Data pipelines to fuel industrial AI applications.
However, challenges remain in efficiently managing and using heterogeneous and untrusted resources across the Continuum. During the workshop, we will present current approaches and cases for Big Data pipelines on Continuum Computing with applicability to Industrial AI, followed by a panel discussion on the long-term Research and Innovation challenges hindering the potential of Big Data pipelines on the computing continuum for solving Industrial AI problems. The participants will produce a position paper based on the contributions and discussions at the session.
Presentations of the session:
Fernando Perales and Radu Prodan presentation (Introduction and panel)
