I watched a TED talk by Aaron Koblin about “artfully visualizing our humanity” but I think his talk could also serve as a “how to” guide for the best way of thinking about the digital humanities. In it, Koblin speaks mainly about accessing large data sets and crowd-sourcing, both of which are topics that might not seem applicable to the humanities. But, one of the things I remember about Professor Michael Witmore’s work is one of our conversations regarding statistics. Professor Witmore was relaying to me a conversation he had with a professor of statistics about trying to find the best method for “artfully visualizing” Shakespeare’s corpus and literature in general. The statistics the other professor recommended for Witmore’s project were similar in kind to the methods used on the human genome project but Witmore’s study of literature was infinitely more complex than DNA. That literature could contain so many variables is, at first glance, hard to conceive of but becomes easier as one considers that individual words, even common “filler” words, are counted as well as phrases, clauses, etc. In this respect, even a contained data set like Shakespeare’s corpus proved to be much hard to visualize clearly and meaningfully than scientific studies. The “largeness” of the humanities then, is a question of scope; a question that has had trouble being answered as scholarship moves into the digital realm.