This past June, I participated in a two-week workshop at Harvard University’s metaLAB called Beautiful Data: Telling Stories with Open Collections. Thanks to a grant from the Getty Foundation, the metaLAB brought together over twenty curators, technologists, educators, and scholars to grapple with how we might use publicly available data from museum collections in our work. In the first week, speakers as varied as digital museum specialists to experience designers to scientists who study vision all pressed us to think of our work in unexpected contexts. In the second week, we took what we’d discussed and applied them to projects of our own.
Over the past four months, I’ve let the ideas and theories of Beautiful Data percolate in my visitor-centered soul, and I’ve come to realize this: although open collections is a movement born in the digital realm, I believe its principles are essential to how a 21st-century cultural institution can reach visitors today—whether virtual, physical, or personal.
What are Open Collections?
“Open collections” is a museum technology term that refers to a museum (or more appropriately, a GLAM—gallery, library, archive, or museum) “opening” all of collections data for anyone to freely use, reuse, or distribute it. In this context, data refers not only to an image of an artwork in a collection, for example, but all of an object’s “metadata” or supporting information, such as artist, time of creation, subject matter, size, medium, and so on. If the collection of your museum is digitally open, you release an API (application programming interface) that allows programmers to easily pull that data into lots of different contexts, such as websites or apps. The idea, according to the OpenGLAM movement, is that it allows “users not only to enjoy the riches of the world’s memory institutions, but also to contribute, participate and share.” (For a more in-depth explanation of museum APIs, check out this blog post from the SFMOMA Lab.)
Metadata sounds like tombstone information—in other words, that basic information that lives on a museum label, and on its own, might not necessarily be that compelling. The magic of open collections data, though, is that through technology, all those individual bits of information can be packaged together and unpacked, visualized and disseminated in different ways. In short, like many of our most successful museum education programs, the cool stuff happens when you release it into the wild and let people play.
Perhaps the most famous example of a museum opening up its collection is the Rijksmuseum, which in 2011 published an API and allowed free access to high-quality images of its artworks. But most stunningly, it not only allowed, but loudly encouraged anyone who wanted to create new interpretations of those artworks, from coffee cups to clothing. They even hosted a contest on the huge handmade marketplace website Etsy.
Another great example is by Florian Kräutli, one of my fellow Beautiful Data participants, who took Tate’s open collections data and visualized it—noticing that over half its collection is by J. M. W. Turner, prompting him into a rabbit hole of discovery into exactly why that is (you can read his blog post on the project to find out more). Museums are supporting this type of play in-house, too: the Cooper-Hewitt team has a treasure trove of ways they’ve used their collections data on their blog, including a search-by-color tool and “Robot Rothko” (which is just as awesome as it sounds). As his final project, Beautiful Data participant Richard Barrett-Small, formerly of Tate, built on the Cooper-Hewitt’s color tool to create Colour Lens, a color visualization explorer for multiple museum collections.
In short, the big idea here is that open collections allow cultural institutions to complete their educational missions: not only showing our objects to as many people as possible (no matter where they are in the world—thanks, internet!), but giving people ownership of our collections and spaces by welcoming them to engage in any way they can dream up.
Investigating Transformative Experiences with Art
Let’s turn back to my personal experience at Beautiful Data. It’s rare that museum staff are ever able to think about the what ifs and why nots, to set aside time to imagine, play, and prototype. Happily, at Beautiful Data, we had two full weeks to do exactly that.
As a visitor-centered museum educator, I think a lot about the humans experiencing our institutions. As a visitor-centered museum technologist, I think about people too, albeit those in the ether of the web—no less real than my students, though often more anonymous. At Beautiful Data, though, we went extremely big-picture—this meant discussions of data visualizations (graphical ways to show stories about data), institutional collecting patterns and preferences, and thinking about how not just staff but organizations could collaborate together through comparing and sharing their collections data.
To be honest, this sometimes frustrated me. As one of two educators in the group, I was always asking, “but what about the people who will actually use this information?” That question was certainly on the minds of other participants, but I came to realize that “users” could just as often mean internal staff members as external visitors.
With all this in mind, for my Beautiful Data final project, I decided to tackle an idea that has been a seed in my work for some time: amassing stories or personal connections with works of art from museum visitors, and seeing what patterns I could find about how people interact with collections. I posted a survey asking people to share their “transformative experiences with works of art,” and waited to see what I’d get.
I was struck by the stories I received. Regardless of length or whether the respondent was a museum professional or a scientist, even if they had only seen the work one time, each story was full of heart—beautiful, nostalgic, sometimes wrenching connections between a work of art and the person’s own life.
Despite a week blissfully surrounded by all things nerdy-tech (read: 3D printers, APIs, and Lytro cameras), instead of building a minimal website or massaging the words into data, I instead was compelled to handwrite key phrases on paper, print out full responses and images of their chosen piece, and pin them to a wall. My project quickly turned into a completely physical installation: a purposefully unscientific data visualization of the responses people had submitted.
Documentary photos of my installation can be seen throughout this post.
Some stories were long, others just a handful of cryptic sentences. Some had art historical, factual descriptions backing up their thoughts; others never looked up a single extra bit of information about the artwork after they saw it. Some ruminated on the object for many years; others were hit in the gut all of a sudden upon turning a corner.
For all that, every single story had two things in common. In each, there was a deeply personal reason behind the individual’s connection to the artwork, and each was written in a tone of reverence—towards the power of these images to arrest a person, to stir up unexpected thoughts or feelings, to stick in their mind for years and years afterward.
To be continued next week in Part 2. This essay originally appeared on artmuseumteaching.com.
Chelsea Emelie Kelly was the Museum’s Manager of Digital Learning. In addition to working on educational technology initiatives like the Kohl’s Art Generation Lab and this blog, she oversaw and taught teen programs.