Visualization Toolkits

As I begin to assemble materials for my spring seminar surveying the digital humanities, I find myself trying to come up with categories, especially for describing arenas of activity. The digital humanities can be quite overwhelming when you are first introduced to them, and because everyone comes to them from so many backgrounds and with so many agendas, it’s hard to separate personal visions from something more synthetic.

Towards the latter, I am trying to think about how to describe some of the things that people regularly do, and I’ll be posting some of my initial thoughts in a series of posts that I will myself later synthesize into something like a syllabus and/or guide. Readers who want to follow along are welcome to do so. I am going to tag the posts with the number for the course, 531, and I will try to update earlier posts so that they turn up under that tag as well.

One of the first things to break out for me is the area of visualization, which is so important that it’s built into most network analysis applications. Visualization, especially dynamic visualization which allows you to adjust your view of the data in various ways, is an essential part of analysis and understanding.

Many of us are used to working with built-in visualizations toolkits like those found in Network Workbench or ORA or even Excel/Powerpoint — Numbers/Pages for those Mac users who eschew Microsoft’s productivity apps and OpenOffice users forgive me for not knowing the equivalents, but R also possesses some remarkable graphical abilities.

None of them can compare to the graphical and/or visualization abilities of two languages build for doing this kind of work: Processing and Protoviz.

Up next: a comparison of the two.

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