We are working at the Malaga Digital Art History Summer School to think about ways that we can visualize or analyze “Big Data” for Art History. I’ve been doing little meaningless tests on the 6000+ objects from the Metropolitan Museum of Art Department of Ancient Near Eastern Art. I thought this could be a fun place to start. We were doing a workflow of importing the data from the Met Github repository, refining/reducing in R Studio, then exporting to Gephi to do network visualizations. I made a bunch of meaningless visualizations that I’m embedding here to discuss with my group on Monday.
This is a network visualization of the object names by material – since some objects share names “cylinder seal” etc they appear as larger dots, but that’s not actually meaningful. At least it looks a little interesting.
I then tried to look at “classification” and “culture” to see if I would see different materials/types of object by culture. With two different visualizations
I also made a visualization of objects by culture – but then forgot somehow that this would lead to totally separate groups because in the database you can only be attached to one culture at a time.
so that’s really ugly, but when you zoom in in Gephi you can see each object number – if somehow that was useful. I don’t know. Anyway, it’s been fun looking at these visualizations, but in the end I think I need to use multimodal networks and think more carefully about questions that could be answered. I actually think that maybe network visualization is not the right method for this dataset, but since we are a group and all working together at the summer school it’s fun to see what I can make together with my colleagues.
Standby for more tests and weird experiments!