I am following an open-tagging approach to tag manually 12,000 images with an average of 5 words per visual. Is there any other more time-conscious approach?
A historian needs time (when the image was made?), space (where the image was made?), author (who made the image?), kind (what kind of image? Picture, drawing, and so on). When we are fulfill that information then we want to know about what is the matter about the image: topic (what about the representation), figures (who or what is represented?), perspective (what is the author's attitude or opinion about the image?).
I'm also in the data analysis phase of my research and have about 2100 images which require 20+ tag each. However I believe I have to tag my photos within my QDA program NVivo, which I've just started learning on: http://www.slideshare.net/mbrownz/pedagogical-design-tools-planning-for-learning-with-purpose#
As far as other photo programs that can tag;
* Pictomio seems good and easy UI (FREE): http://www.pictomio.com/Default.aspx
*Adobe Lightroom has the ability to tag multiple images at once, which could cut down on your time, i.e. if there are 1000 images that display a hat, you can tag one with the word hat then group select the rest and snyc the metadata so they are all tagged the same (this may take some trial and error with different variations of words though)
One thing to keep in mind is what will you do with the images once they've all been tagged? Feed them into a QDA? Then you must make sure you have cross-program compatibility; one can't assume that the meta data assigned by one program can be read by another.
Given the very large amount of images you have you may also consider using crowdsourcing to tag the images:
http://newsoffice.mit.edu/2012/making-crowdsourcing-easier
What are the images your're studying?
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