The investigation of physical phenomena generally implies a measurement of the relevant quantities through the detection and the processing of a physical signal, and the development of an interpretative framework of such measurements that allows to model the physical system and predict its evolution. The former process represents the experimental side of the investigation, and is based on the deep knowledge of the mechanism of interaction between a sensing device and the physical system, the design of the acquisition device and of the data handling strategy, as well as the pre-processing and post-processing of the data into a final scientific measurement. The latter represents the theoretical/interpretative side of the investigation, and amounts to develop a physical model and compute its predictions for other measurable quantities. Due to the complexity of the models and/or of the physical systems, this step often requires the use of sophisticated computational methods. With a focus on the big data complexity and the computational aspects, the School aims at discussing this pipeline across various Physics subdomains.