Orateur
Description
With Machine Learning techniques being applied at larger and larger scales in high-energy and astroparticle physics, workflow management is gaining attention as one area where careful design and implementation are crucial to the success of a solution. "Workflow management" is indeed a broad term itself, with different meanings. Presentations on specific approaches at IWAPP have explored various aspects, ranging from more hardware-oriented studies to mathematical techniques and project lifecycle management; at the same time, it has been shown that Machine Learning, while originally well grounded in offline data processing, is moving closer and closer to instruments, possibly providing (quasi) real-time decision and data acquisition steering capabilities with online reconstructions using trigger objects rather than raw data. At the other end of the application spectrum, Machine Learning is being used to provide classification criteria for libraries of datasets. The discussion is expected to develop about tools and best practices to ensure that the solutions are flexible and future-proof.
