Here’s a roundup of how people have used MoMA’s data so far.
Oliver Roeder of FiveThirtyEight took us on a data-driven dérive through MoMA’s galleries, with .
Scientist, teacher, and programmer Eamon Caddigan . Our dataset didn’t actually include artist gender (we’re working on it!), so Eamon used .
Looking at acquisition dates, humanities professor Steven Lubar asked and Eamon Caddigan concluded that Design researcher Florian Kräutli used the data to produce . (Thumbnail URLs are coming soon, Florian.)
Writer and technologist Allison Parrish used our data to create the Twitter bot . It randomly recombines data from MoMA to generate new titles and medium descriptions for artworks. Fusion .
Another Twitter bot, by technologist Ross Goodwin, posts alternate versions of MoMA collection items every two minutes.
Srini Kadamati of Dataquest.io used a small subset of the data to . Technologist and O’Reilly author Bob DuCharme took his data wrangling further into what he calls “feature engineering”, . It’s no secret that our data is a work-in-progress, featuring many quirks and gaps. We loved Bob’s reference to the .
Finally, for now, MoMA’s collection data is being incorporated into the Digital Public Library of America, and Wikipedians made Wikidata properties P2174 and P2014, creating links from Wikipedia to more than 3,500 artists and 2,ooo artworks.
What did I miss?
[Updated October 26 2015 in response to comments.]
