Many software packages make it relatively easy to create visualizations of complex networks of data, but often produce hairballs that tell us more about the visual layout algorithm than the structure of the network. Martin Krzywinski has proposed an alternative, called hive plots: lay out your nodes along a series of axes that you know have meaning in your network, and explore the network visually from there. Mike Bostock, predictably, has done gorgeous interactive work with Krzywinski’s idea in the d3 javascript library.
I created my first hive plot this morning using d3. The screen shot above illustrates a project by Megan Whitacre (Holy Cross ’14) annotating a series of illustrated inscriptions for use in teaching introductory Latin. The five axes are (clockwise beginning from the blue axis at the top) 32 broad grammatical concepts, 71 narrower topics about the morphology of substantives, 55 topics about verbal morphology, 9 syntactic topics and, along the purple axis, 103 images. All of Megan’s annotations are expressed with CITE URNs; this makes it straightforward both to gather all references to the same image, or to apply her region of interest to highlight areas of the image. d3 practically begs for interactive displays, so you can highlight nodes or edges to see further information, or can click on image nodes to see the image with linked, highlighted areas for all references to the image.
There is plenty of room for improvement. Selecting a node or edge really out to select all direct connections to it as well, and hovering should use Megan’ rdf:Label values, instead of the raw CITE URN to identify the node, to name two obvious desiderata. But as an initial effort put together between second cup of coffee and lunch break, it’s hard to be disappointed with it. It underscores for me that as our tools improve, it becomes more and more important to have properly structured and properly citable data.
(The screen shot is linked to a live version of the graph.)
No comments:
Post a Comment