Networks are abstract and ubiquitous data structures, defined as a set of data points and
relationships between them. Network visualization provides meaningful representations of …

Most real‐world networks are both dynamic and multivariate in nature, meaning that the
network is associated with various attributes and both the network structure and attributes …

Interaction is fundamental to data visualization, but what “interaction” means in the context of
visualization is ambiguous and confusing. We argue that this confusion is due to a lack of …

Going beyond established desktop interfaces, researchers have begun re‐thinking
visualization approaches to make use of alternative display environments and more natural …

From social networks to brain connectivity, ego networks are a simple yet powerful approach
to visualizing parts of a larger graph, ie those related to a selected focal node—the so-called …

Matrix visualizations are a useful tool to provide a general overview of a graph's structure.
For multivariate graphs, a remaining challenge is to cope with the attributes that are …

The visual analysis of multivariate network data is a common yet difficult task in many
domains. The major challenge is to visualize the network's topology and additional attributes …

Large, complex networks are commonly found in many application domains, such as
sociology, biology, and software engineering. Analyzing such networks can be a non-trivial …

The visual analysis of multivariate network data is a common yet difficult task in many
domains. The major challenge is to visualize the network's topology and additional attributes …

Several techniques for visualization of dynamic graphs are based on different spatial
arrangements of a temporal sequence of node-link diagrams. Many studies in the literature …