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DBpedia and ULAN both seem to have richer sets of relationship properties than Wikidata, so they might be more useful resources to query. Robert Henri’s DBpedia page, for instance, has “movement”, “training”, “influenced”, “influenced by”, and “seeAlso” properties. Again, however, pulling data from DBpedia may be beyond my technical capacities at the moment.
The first step for applying this process to Provenance would be to export the “imoec_founding_collection_purchase” package in TMS as a csv file. I haven’t been able to figure out how to generate csv files from TMS yet, but this would be a starting point. I’m just learning to search fields and export JSON files from csv files, so I should at least be able to start the process of cleaning a Provenance csv file.
Python doesn’t seem to be currently installed on my workspace computer, and I keep getting denied permission to install it on my user account. I’m not sure whether it would be better to contact Whitney IT or simply to use my laptop for Python programming. I’m more familiar with working with a Mac environment, so working on my laptop might be easier.
Of note: the Carnegie Museum of Art was recently involved with a data-related project focused on provenance. It lead to the creation of a Ruby library for generating provenance records:
http://www.museumprovenance.org/
https://github.com/arttracks/museum_provenance
