Tag Archives: data

Photograph of Rousseau installed at MoMA

Installation photograph from The Museum Collection of Painting and Sculpture exhibition, held 20 June 1945 to 13 February 1946

On September 7, 2016, The Museum of Modern Art (MoMA) in New York cracked open a new repository on the code repository service, Github. In addition to the release of their popular collection dataset, the museum also made the unprecedented decision to share the exhibition history of the museum (from 1929 to 1989), which also included a ton of archival material like press releases, installation photographs, and catalogues. You can see the official version on

MoMA asked Good, Form & Spectacle to make a spelunker to showcase this data, and we were thrilled to oblige.



First Steps

As with all our previous spelunkers, the first step we usually take is to map out a basic plan for the information and how you’ll move around in it. This is often a basic List -> Item pattern, where List can be made up from any of the main data elements. In the case of MoMA, that was Exhibitions, Roles, People/Orgs, and Departments. From each list view, you can move to a single instance of that type of thing, and from that single instance, back out into others, like from an exhibition to the year it happened, or to an artist in that exhibition. (We also get a Python project running on Heroku, and pop our own first commits on Github.)

The main reason we enjoyed making the MoMA Exhibition Spelunker so much was because the data was of a different nature to a collection dataset. As well as listing each exhibition over that period, the data also shows all the people who were involved, both the artists, but also, interestingly, museum staff and other collaborators. We’ve looked a little at how metadata can represent institutional dynamics with Week 1 of the What’s in the Library? project with Wellcome Library, but this was altogether more fine-grained. Who are the actors in this institution? Can  you see their influence?

First Impressions

So, once we have the basic List -> Item scaffold in place, it’s really a matter of trying to answer the questions that come up for us as we poke around all the corners of the data. One of the first simple visuals we added as the basic timeline, to show quickly and clearly what happened, and when.


Straight away, even a simple graphic like this asks questions. What’s that peak in World War II? Why the dip in the 50s? Why was 1978 such a full year?

It’s important to say at this point that a lot of what I’ll write next about what I discovered in the MoMA Spelunker is pure conjecture and presumption, based on looking at this data quite a lot. It may not be true, at all. (See Open Data, Assumptions and Naïvety below.) 

The Museum & People Dynamics

We don’t often get to see or know the dynamics and politics that go on within the walls of a museum. It can be such a designed space, all about the art or objects, that often the people who made an exhibition come true are almost entirely invisible. It was a real pleasure to work on this data from MoMA specifically because it isn’t about the art, but about the people. When we first began the project, I was keen to be able to show the art, but that desire was quickly supplanted by interest in, and display of, who was doing what.

One of the visualisations we made was about directors of departments, how long they were directors, and in some cases, showing where people went as they moved around the museum, in some cases in careers spanning 40 years. You can see in this screenshot what we can highlight a single individual as they move around too, so you can see who skipped where and when, like John Elderfield


It was bordering on titillating to imagine who might have worked together and how such long term tenures really did shape the museum as it is today. But, it’s also crystal clear that a little map like this can reveal nothing about why people moved around. You’ll need to look in the Archives to learn those stories.

MoMA Characters Emerge

I was enjoying the way that showing this kind of data over time helps you spot blobs and trends and gaps in the data. I was interested to try to uncover whether we could show who the key staff were that really got MoMA off the ground in the early years. By taking a role – Curator – and drawing it over time, you can see quickly see who was kicking things off, in this case, the founding director, Alfred H. Barr, Jr., curated 36 exhibitions, and worked there for about 40 years.


Something interesting happens when you change how that list is sorted. We can show the same data, but order by who curated the most exhibitions, to get a really different picture that shows the curators who’ve worked on the most exhibitions, and how much they made in any given year. It’s there that you start to notice the effort of curators like William S. Lieberman, who led three different departments over his career, or Dorothy C. Miller, who worked at the museum for about 30 years, and was head of the Department of Painting and Sculpture for a relatively short time, too. Did they work together? Did they like each other?


We liked this “most appearances” view much more, so set that as the default.

This list view is cool too, when you’re looking at artists. There’s a lot of info squished into that single list view, and the overall impression is mostly that MoMA has an incredible collection full of heavyweights (and very good relationships with collectors and other museums), and shares it with the world a lot! Here are the most exhibited artists in the 1929-1989 data… could you infer Jasper Johns blasted on to the scene at some point there?


One small design thing I introduced was to show a small  symbol in big lists of people, so you could spot women quickly. This revealed a little gap in the data, where gender isn’t always noted. Since perfect is the enemy of good, rather than remove the feature, I’m trying to help by slowly making additions/corrections to a copy of the data, which MoMA is welcome to. (Want to help?)

World War II and The Responsive Museum

defenseflyer008Something that piqued my curiosity almost immediately was about how the museum operated in World War II, 1939-1945. They were exhibiting a lot, and browsing 1942 and 1943 in particular, there were clearly lots of exhibitions related to the war.

I first noticed the annual exhibitions called Useful Objects of American Design under $10.00 that opened in 1939, and repeated for a few years thereafter. I found myself wondering if this was austerity-related, but then realised I didn’t know the equivalent of $10 in today’s money! Nevertheless…

Then I noticed several others that were much more specific to war, starting to emerge in 1940 and many more in 1942/1943, and beyond, like War Comes to the People: A Story Written With The LensNational Defense Poster CompetitionArt in War: OEM Purchases from a National CompetitionWartime HousingRoad to VictoryCamouflage for Civilian DefenseUnited Hemisphere Poster CompetitionThe Museum and the WarNational War Poster CompetitionArt Education in WartimeWar Caricatures by Hoffmeister and PeelAirways to PeaceMagazine Cover Competition: Women in Necessary Civilian Employment, and more.


Airways to Peace (and a cool interactive dymaxion globe!)

With a little further digging beyond our dataset, I quickly discovered that “numerous exhibitions at The Museum of Modern Art were produced in collaboration with the United States government,” as it continued to exhibit the very best in modern art, including Starry Night, which MoMA acquired in 1941, and exhibited soon after.


I simply don’t know how data like ours could possibly show that Victor D’Amico chaired the Committee on Art in American Education and Society, which established as “art education’s answer to Fascism and its contempt for creative art. We hope to mobilise the art educators and students of America, combining all their art efforts, large and small, throughout the nation to work for victory.” It’s just one or two steps away from his basic data, and you always have to stop making new columns in data at some point, don’t you?


The committee worked throughout the year to keep art on the educational agenda. There’s a lot more background about the museum and the war available in this archival finding aid online: The Museum and the War Effort: Artistic Freedom and Reporting for “The Cause”. (It’s worth a read.)

I have to say it makes me wonder how and if museums in the USA (and elsewhere) are mobilising to produce a “vast program of art activity” in this way to combat the 45th president. Ahem. In any case, I actually removed a bunch of other “this was interesting” and “I enjoyed this” links and stuff. You can find your own way!

What did the critics say?

NATURE and social satire are the themes of two current shows here. Both are important and well worth seeing.

Jacob Deschin, on Elliott Erwitt: Improbable Photographs

Remember mashups? When publicly accessible code-level interfaces (or APIs) became a thing back in the day, the fantasy was that all manner of mashups could be made to combine and recombine data from all over into compelling new presentations.

One of our early ideas for this spelunker was to try to bring in content from the fabulous New York Times archive, a treasure trove of history around New York City and its surrounds from 1851 to the present. We knew that The New York Times regularly reviews events and exhibitions at MoMA, so it was simple step to try to combine that with the MoMA exhibition data. Luckily, too, the MoMA team had already done a lot of the work to connect exhibitions to articles, which was hugely helpful.

Could we show what The New York Times critics said about MoMA through the twentieth century? Yes! Critics such as Edward Alden Jewell, who was watching from the start in 1929, or Jacob Deschin, who often wrote about photography exhibitions from the late 1940s to the late 1960s, also form part of the fabric of the exhibition history at MoMA.

(Note that you can’t see full articles unless you’re a subscriber. We can show first paragraphs, which is a start.)

Open Data, Assumptions & Naïvety

This work for MoMA has been interestingly different from previous spelunkers we’ve made. In other projects, we’ve made exploratory interfaces into object-level metadata, which is (arguably) simply factual, representing objects and their attributes. While there may be errors or omissions in this kind of metadata, each object is as well-described as possible. Sometimes, viewing this data in the aggregate can bring insights — like seeing instantly that prints form the largest group of things by type at the Victoria & Albert Museum — but there’s really not much ‘colour’ to it.

Part of the provocation of the spelunker concept is to challenge the notion that people know what they’re looking for when they encounter a new museum’s collection, and I’m wondering if that could be extended to museum datasets. It seems to me that “drawing” this data makes it easier  to hypothesise about and ask questions of than examining a big .CSV file. You follow your instincts or an image that appeals or a person you recognise or a theme you’re into, and, I think, start to form your own opinions pretty quickly. The challenge is that this metadata can be quite rich, but, at least in our experience so far, also pretty superficial, so the picture that’s drawn for you is just a surface view. Perhaps though, it’s like a physical exhibition where you don’t read any labels (or there aren’t any), and you’re left to make your own judgements, some of which may be wrong, but all are personal.

As we were fleshing out the interface to the MoMA spelunker, I found myself making all sorts of assumptions about the institutional dynamics at the museum related to who was working when, and why they might have moved around, their areas of interest or speciality, and things like that. I’d written about some of that sort of stuff on the About page, but the kind folk at MoMA archives were good enough to let me know that some of those assumptions were just plain wrong! Maybe it was more that the data we were able to display only gives you a tiny glimpse into the actual dynamics, and it’s simply a must to explore more deeply with experts or other source material. I don’t want to draw wrong conclusions, and experts in house, who live with this information day to day, surely don’t want to express things that are wrong. Of course not. I think what I’m coming around to is that these sorts of explorers help orient viewers towards questions they’d like to answer, once they’re acclimatised to the terrain. That seems good!

More broadly speaking, we’ve now made six spelunkers at G,F&S, and it’s probably about time I had a proper think about how well they’ve worked and whether they’re useful. More on that later…

The team for this project was George Oates (design, project lead), and Phil Gyford (engineering). Thanks, Phil!


It’s pretty late on a Friday afternoon, possibly the dumbest time to launch something, but, my conspirators and I decided to only work on this this week, so, we kind of have to launch it now.

The thing is called Two Way Street, and it’s a new way to explore The British Museum collection. It’s truly a museum of the world for the world, and we think Two Way Street is fantastic for looking around. Our team was George Oates, Tom Armitage, Frankie Roberto, with a cameo data-munging appearance by computer scientist, Tom Stuart. Thanks also to Harriet Maxwell and Tom Flynn for working on the (unsuccessful) proposal to NESTA for funding, Felix Ostrowski for RDF-to-JSON advice, and Barry Norton for restarting the BM SPARQL endpoint.

Two Way Street is basically an exploded view of the catalogue. Once we’d processed the big catalogue into a format that was easier for us to work with, we built just a few simple template views on top of the catalogue. We also skewed the user experience towards learning about the acquisition history of the museum. There are some really interesting trends and people involved in the formation of the institution. The British Museum was founded in 1753, and is the world’s first public museum.

Here’s the home page, where we introduce the first of a handful of visualisations, acquisitions over time, by decade.


We’re also able to display a bunch of facets we selected as interesting. You can use them as leaping-off points into the collection. There’s another subtle visualisation there to show you which facets are well-understood in the metadata.


Here, you can see a list of all the people (or institutions) who found, excavated, or collected things…


Like Chloe Sayer, who found/excavated/collected 6,296 things in the later decades of the Twentieth century…


It’s a Ruby, Elastic Search, Heroku, AWS-y thing. We’re also making use of the British Museum’s data dump from last August, and hitting their SPARQL endpoint (possibly a bit harder than everyone is used to). I like to think we’re some kind of “cultural white hats” that might actually be able to constructively help the museum to understand and develop the infrastructure it needs to serve more external development.

There’s a little more about it all on the site’s About page, if you’d like to go and have a look. Tom’s going to follow up, too, with some thoughts on using Elasticsearch instead of a database, which we all through was pretty cool.

I’m sitting here in my kitchen after a whirlwind trip to Paris for Europeana Tech 2015. I’m making vegie stock, drinking a glass of delicious oatmeal stout, and finally realizing I like to cook to relax. I took the Eurostar for the first time, and bought some stinky cheese from the station on the way back.

It was a great few days, Paris was gorgeous, it was nice to meet some new folks and see some old friends, and I think the talk went well. I’ll be curious to compare the video with my notes. Perhaps one day I’ll try reading directly from notes like the old days, but this was not that. I did like the quick lecture from Jonas Öberg though, where he just spoke to us.

The main thrust of my speech centered around an appropriation of Kevin Lynch’s brilliant The Image of the City. I likened the giant metadata clearinghouses that exist online today with the odd huge ghost cities in China and now Angola, and how, if we adopt the techniques of designing the clues, keys and paths we are so familiar with in our cities to the data landscape — particularly in the cultural heritage realm — we might start to escape the tyranny of the search box. Google is great for searching everywhere for anything, but that’s not what you’re doing when you come to a museum.

Anyway, here are my slides from Friday:

And if you’d like to read it as slides with notes, you can download this 80MB whopper PDF.

Some personal highlights for me were:

  • Meeting the Executive Director of Europeana, Jill Cousins. Always great to meet women leaders, and she’s been at at the helm since it started.
  • Hearing Jaap Kamp’s no bullshit stance on cultural data and the dominance of search as a (misplaced) mentality for exploration.
  • Seeing old mates like Andy Neale, Dan Cohen and Jon Voss. Nice to call them old mates, too.
  • Meeting Ben O’Steen who’s at British Library Labs, which I’d not heard of but plan to haunt. I particularly liked his cheap solution for providing massive data at hack meetings: a big hard drive, a fat wifi pipe and a router. I’m always a fan of people who make tiny flimsy bridges that are only supposed to last for a short time.
  • Sparring with Dominic Oldman about RDF. It’s not clear that it’ll be possible for me to use his work in a project I’m working on. We’ll hopefully meet in the next week or two to see what can be done.
  • Hearing from Tim Sherratt in Australia and enjoying his vibe about “discovery engineers” and the interesting, engaging work that happens at tiny scales versus the mythical mega project.
  • Giggling at the frankly tone-deaf speaker from Google Research who had no idea who we were and made no attempt to learn. Hey, guy… if you’re going to give a speech, try not to say “I have no idea what it is that you do, but let me tell you about things I call…” Seriously, it’s rude and patronising.
  • Navigating Paris effortlessly thanks to Citymapper. Excellent.
  • The overall theme that huge is starting to feel inaccessible. Like having sex with The Hulk. Ahem.


The meeting was held at the Bibliothèque nationale de France, which proved to be an interestingly inaccessible building. Lots of us were disoriented inside, even after a day, doors were hidden with flat facades, push then pull to get through two doors, literally scale-mail walls, security turnstiles to enter the stacks… it was all there. An interesting counterpoint that I now wish I’d tried to incorporate into the talk, but, oh well.

It’s an interesting time for this group. There’s so much work going on trying to help the computers understand the wily, complicated humans that describe our heritage. It’s SO COMPLICATED because nobody ever describes things in the same way. Well, they probably never will.