Methods, challenges, and applications ... planarity always strikes back!

Description and goals | Schedule | Speakers | Organizers

In the Big Data era, several real-world domains produce an incredibly vast amount of data that naturally exhibit a networked structure and can thus be modelled in graph-theoretic terms. Notable examples include social networks, financial transaction streams, and biological networks. Visualization plays a crucial role in the critical process of extracting the relevant information and of emphasizing the underlying structure of such complex and massive networks. In fact, human-eye’s ability to extract patterns and detect anomalies remains unsurpassed by any technological solution. The Graph Drawing research area provides the theoretical foundations for network visualization.

The aim of this workshop is to provide an overview of this research area, with a focus on the most relevant models in the domain of Constrained Graph Layouts and their applications. Starting from the seminal subject of Graph Planarity, the workshop will present notable models that have emerged as prominent tools to address the challenges posed by the visualization of real-world networks. This includes Hybrid Visualizations, Beyond-planar Drawings, Linear Layouts, Simultaneous Embeddings, and Clustered Graph Representations.

Although real-world graphs are often far from being planar due to their locally-dense behaviour, planarity elegantly comes to the rescue. On one hand, several advancements in the research on such models build upon algorithmic tools and combinatorial properties devised in the vast theory of planarity. On the other hand, it turns out that many of the above models can be expressed as the search of planar drawings satisfying ad-hoc combinatorial properties.