The Cleveland Museum of Art is a world-renowned art museum with a substantial collection of over 61,000 artworks. In January of 2019, they launched their Open Access Initiative in which they made over 30,000 public domain works and metadata for their entire collection public and downloadable (GitHub). Metadata includes title, description, artist, year, and department, among other details. As part of the Open Access launch, CMA asked Pandata to participate in demonstrating the power of such a data set. Using natural language processing and data visualization techniques, Pandata used the text descriptions from all art that had one (approximately 10,000 works) to visualize how we write about art across time and cultures. Learn more
Museums have a tremendous amount of qualitative data. Natural language processing can identify themes and patterns at scales in collections that can help curators uncover powerful patterns in art history. Machine learning can create amazon-style recommender systems to introduce the general public to lesser known art pieces, developing an appreciation for the arts in a fun and engaging way.
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