From the site:
In conclusion, there are several “take-aways?? with regard to the use of network visualizations. These “take-aways?? will come in the form of questions which can be used when considering using a network visualization to communicate knowledge. 1) Is the data you are trying to represent psychologically predisposed to being represented on a network? Novick and Hurley (2001) research suggest that people may be more psychologically predisposed to think of networks as good at representing single set of objects, and those more technically inclined to think that set should be relatively small in size. 2) Does your user population thrive in structured or ill-structured environments? If they prefer structure, the networks should invoke common region, or nodes should be clearly boxed together. If they prefer ill-structured environments, explicit grouping of nodes should not be used (Chmielewski, Dansereau, & Moreland, 1998). 3) Are there concerns about motivation? Node-link maps can be more engaging to create and to study than traditional texts and should be considered if motivation is an issue (Hall & O’Donnell, 1989; Czuchry & Dansereau, 1996). 4) Do the relationships between nodes and links need to be nuanced? If so, the node-link map may not be an appropriate tool and text may be a better alternative. 5) How complex is the data you are trying to represent? If the data is complex, one should be aware that comprehension may decline if too much information is placed on the visualization (Kosslyn, 1989). This might be counteracted by providing tools for navigating the map, such that information can be removed, highlighted and zoomed-in on. 6) Do you need your user population to remember something? Network visualizations lead to better free recall than texts, lists and outlines (Nesbit & Adescope, 2006). However, the research which correlates node-link maps to recall ability is more substantial where people create their own node-link maps versus simply studying a pre-completed node-link map.