The visualization of complex data sets is of essential importance in communicating your data products. Beyond pie charts, histograms, line graphs and other common forms of visual communication begins the reign of data sets that encompass too much information to be easily captured by these simple data displays. A typical context that abounds with complexity is found in the areas of text mining, natural language processing, and cognitive computing in general; such a complex context for data presentation is pervasive in an attempt to build a visual interface for products like semantic search engines or recommendation engines. For example, statistical models like LDA (Latent Dirichlet Allocation) enable for a thorough insight into the similarity structure across textual documents or vocabulary terms used to describe them. But as the number of pairwise similarities between terms of documents to be presented to the end users increases, the problem of effective data visualization becomes harder.