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We consider hypergraph visualization that represent vertices as points and hyperedges as lines with few bends passing through points of their incident vertices. Guided by point-line incidence theory we show several theoretical results: if every vertex is part of at most two hyperedges, then we can find such a visualization without bends. There exist hypergraphs with three vertices per hyperedge and three hyperedges incident to each vertex requiring an arbitrary number of bends. It is ETR-hard to decide whether an arbitrary hypergraph can be visualized without bends. This only answers some interesting questions for such visualizations and we conclude with many open research questions. 

Network visualization is one of the most widely used tools in digital humanities research. The idea of uncertain or “fuzzy” data is also a core notion in digital humanities research. Yet network visualizations in digital humanities do not always prominently represent uncertainty. In this article, we present a mathematical and logical model of uncertainty as a range of values which can be used in network visualizations. We review some of the principles for visualizing uncertainty of different kinds, visual variables that can be used for representing uncertainty, and how these variables have been used to represent different data types in visualizations drawn from a range of non-humanities fields like climate science and bioinformatics. We then provide examples of two diagrams: one in which the variables displaying degrees of uncertainty are integrated/pinto the graph and one in which glyphs are added to represent data certainty and uncertainty. Finally, we discuss how probabilistic data and what-if scenarios could be used to expand the representation of uncertainty in humanities network visualizations.