A Taxonomy for Uncertainty in Static Geo-Located Networks

Static graphs are analysed in various domains such as social science, finance, or communications. Often, these networks are geolocated, i.e., the nodes/edges have a geographic location. For example, in social networks, the connected people have a home location. Experts strive to gain knowledge about the network structure and its geo-location. They often use visualization for this purpose. Static geo-located graphs may include uncertainty. The uncertainty can affect both graph’s nodes and edges. For example, uncertainty may be with regard to the existence of links between nodes, or the node locations. For the visualization of geo-located graphs incorporating uncertainty, it is important to define the types of uncertainty that may appear in networks and to distinguish the various degrees of uncertainty. Although various typologies of uncertainty of geo-located data have been proposed, graph component is largely missing. Therefore, we extend current taxonomies with graph aspects.