Minimally invasive robotic surgery has marked a revolution in clinical practice, and a significant aspect of its future evolution involves analyzing endoscopic visual data to develop intelligent assistance functionalities. One of the main challenges is understanding the surgical workflow, which involves recognizing activities at multiple levels of granularity, from macro-level procedural phases to micro-level atomic actions. This work addresses this challenge by focusing on a paradigmatic and complex task for robotic surgery: suturing. The first contribution is the creation and annotation of the LUMICS (Multi-Level Understanding of Minimally Invasive Colon Suturing) dataset, consisting of 15 videos of suturing procedures on porcine colon, performed with the da Vinci Research Kit (dVRK) system at the MITIC laboratory, Department of Surgical Sciences, University of Turin.