It's been six months since The Met launched its Open Access initiative, which made available all 375,000+ images of public-domain works in The Met collection under Creative Commons Zero (CC0). During what is just the dawn of this new initiative, the responses so far have been incredible.
- More than 90% of the CC0 images have been uploaded to Wikimedia Commons, we hosted our first Wikimedia Edit-a-thon and Met Open Access Art Challenge, we've witnessed a 500% increase in new Wikipedia articles featuring Met images (6,598 as of June 2017), and traffic to the online collection from the Wikimedia platforms has increased by 10%. Richard Knipel, our Wikimedian-in-Residence, recently blogged about this program.
- The Met's content makes up two-thirds of the searches on Creative Commons Search, and it's reassuring to see that Van Gogh, Monet, Botticelli, and Picasso all rank as high as "cat" and "dog" as search terms. Learn more about Creative Commons' new CC Search feature on their blog.
- Overall traffic to the online collection has increased by 17%, image downloads have increased by 64%, and we're seeing that users who download an image have a significantly stronger engagement with the collection: they spend five times longer on the site, and visit five times more pages.
- We've also seen lots of playful uses of the CC0 content—Face-Swap The Met was a favorite—as well as those that take a deep dive into the data; FiveThirtyEight's analysis, "An Excavation of One of the World's Greatest Art Collections," was a highlight.
To further develop the Open Access initiative, I'm delighted to mark the six-month milestone of Open Access at The Met with the addition of The Met's public data set to Google's BigQuery platform.
Google BigQuery is a data warehouse for large-scale data analytics, giving users access to a range of public data sets on which you can run queries in SQL. The Met's data set is the first to be added to the platform by a museum.
We're particularly excited about the ability to connect data in BigQuery to Google's Cloud Vision API, thus enabling analysis of the image content. Sara Robinson, a data analyst at Google BigQuery, has written a fascinating blog post about what happens when art meets big data and the Cloud Vision API. We're now interested to see what other types of visual analyses the community starts doing with the images through the BigQuery platform. Thank you to everyone at Google BigQuery for their interest in The Met's CC0 data, and for making it available through their platform.
Google BigQuery now joins Artstor (part of ITHAKA), Wikimedia, Creative Commons Search, and GitHub as platforms where The Met's CC0 images and data are accessible for a growing community to use creatively or for personal enjoyment.
Learn more about The Met's Open Access initiative.
The Met's Open Access initiative is made possible through the continued generous support of Bloomberg Philanthropies.