This paper surveys visualization and interaction techniques for geospatial networks from a
total of 95 papers. Geospatial networks are graphs where nodes and links can be …

Well-designed data visualizations can lead to more powerful and intuitive processing by a
viewer. To help a viewer intuitively compare values to quickly generate key takeaways …

Undirected graphs are frequently used to model phenomena that deal with interacting
objects, such as social networks, brain activity and communication networks. The topology of …

Network data, represented by graph-based structures, are used in a variety of applications
such as social networks and disease complication networks. A crucial task in many …

Hybrid visualizations mix different metaphors in a single layout of a network. In particular, the
popular NodeTrix model, introduced by Henry, Fekete, and McGuffin in 2007, combines …

This study aimed to investigate water quality and identification, prioritization and network
analysis of the stakeholders of the Anzali International Wetland, Iran. In the wetland …

Representing and analyzing structural differences among graphs help gain insight into the
difference related patterns such as dynamic evolutions of graphs. Conventional solutions …

Visually identifying effective bio-markers from human brain networks poses non-trivial
challenges to the field of data visualization and analysis. Existing methods in the literature …

Functional and structural connections vary across conditions, measurements, and time.
However, how to resolve multi-relational measures of connectivity remains an open …

Graph neural networks (GNNs) have witnessed an unprecedented proliferation in tackling
several problems in computer vision, computer-aided diagnosis, and related fields. While …