Smart Visualization Annotation by Enrico Bertini.
From the post:
There are three research papers which have drawn my attention lately. They all deal with automatic annotation of data visualizations, that is, adding labels to the visualization automatically.
It seems to me that annotations, as an integral part of a visualization design, have received somewhat little attention in comparison to other components of a visual representation (shapes, layouts, colors, etc.). A quick check in the books I have in my bookshelf kind of support my hypothesis. The only exception I found is Colin Ware’s Information Visualization book, which has a whole section on “Linking Text with Graphical Elements“. This is weird because, think about it, text is the most powerful means we have to bridge the semantic gap between the visual representation and its interpretation. With text we can clarify, explain, give meaning, etc.
Smart annotations is an interesting area of research because, not only it can reduce the burden of manually annotating a visualization but it can also reveal interesting patterns and trends we might not know about or, worse, may get unnoticed. Here are the three papers (click on the images to see a higher resolution version).
(…)
What do you make of: “…bridge the semantic gap between the visual representation and its interpretation.”?
Is there a gap between the “visual representation and its interpretation,” or is there a semantic gap between multiple observers of a visual representation?
I ask because I am not sure annotations (text) limits the range of interpretation unless the observers are already very close in world views.
That is text cannot command us to accept interpretations unless we are already disposed to accept them.
I commend all three papers to you for a close reading.