Titolo della tesi: Enhancing Visual Analytics Support to Multilayer Network based Data Analysis
This thesis represents a first step in supporting visualization tasks for multilayer networks, working on its modelization and researching fit visual abstractions to support the Visual Analytics Knowledge generation model fully. The thesis contributed two ways of modeling the multilayer network data, proving their generality and fitting two different application domains. It also successfully investigated ways to support the fluid exploration of intra-layer and inter-layer data for the most challenging domain of biomedicine. Finally, it investigated the enhancement of visual interpretation and interaction with visual representation coming from the application of data visualization techniques on these data, allowing to identify solutions to support the intended users better.