Arm’s Length Data?

I’ve spent today looking up the 2019 Annual Reports of all the Arm’s Length Organisations that DCMS gives grant-in-aid funding to. I’ve put some figures I think are involved in my learning about Who Needs It Less?

I’ve made a Google spreadsheet called DCMS Arm’s Length Orgs snapshot – 2018-2019, and anyone can view with this link. Please tread carefully! THERE MAY BE ERRORS. This is rough work, comments welcome!

These are big numbers. I’ve collated a few different fields per organisation I think are interesting:

  • Total income (for that year)
  • Total expenditure
  • Net income (which may be in the red)
  • Fixed assets (which likely include tangible, intangible, heritage, and certain types of investments)
  • Current assets (like stocks, debtors or cash)
  • Grant-in-aid figure if I could find it in the Annual Report (and there’s a second sheet in the spreadsheet that gets that number per org from a doc I found from Parliament, which is linked as the source)
  • Endowment if that figure is noted separately

From this basic by-hand aggregation, you can see stuff like the BBC’s Total Income in 2018 was £4,889,000,000 or National Gallery had the highest Net Income at £15,400,000.

Then I added two % calculations:

  1. Current Assets as a percentage of the Total Income for that year, and
  2. Grant-in-aid as a percentage of the Total Income for that year

Now, I’m not stating anything resembling an approach to trying to figure out which orgs to support and how, but, I’m wondering about these two percentage figures… could they be some measure of health or stability? As Frankie rightly commented on my previous post about this, the Fixed Assets held by our great institutions are probably basically irrelevant, since they’re practically priceless. But maybe if you can say something like the Imperial War Museum has Current Assets that could cover about 64% of its annual income, does that get us anywhere? Or that Royal Armouries has 12% coverage from its Current Assets?

What if we look for orgs that have current (or, more fluid) assets that cover less than 20% of their annual income for 2018 and help them first? Or 50%? Better yet, we could filter that list to deliberately favour BAME and LGBT and disabled-led orgs.

What if the government (and our society) is able to seize this moment to actively work against the preferential structures in its own system? It could actively generate assets for littlies. Grant them 1-3 years equivalent to their 2018 income, and give them an endowment equal to the average of the Arm’s Length orgs, which by my rough calculations is 47% of 2018 income in the bank. That would be a reflection of the healthy situation DCMS has built with their Arm’s Length program, would it not?

I thought I’d have a look at NPOs next, poking at that Current Assets idea. It can be enlightening to see who has no wealth, when that’s such a marker of systemic exclusion.

Notes on data creation:

  • I’ve left comments on cells if something odd or there’s extra info or detail
  • Sources are individual org’s annual reports, linked in Column B
  • If there’s an overarching group, I’ve used that number
  • Director’s Pay is the total package, salary + pension etc
  • DCMS grant in aid is as noted in the annual report
  • I’ve basically looked for what appears to be the same numbers across all the annual report documents – that’s mostly the Balance Sheet and Financial Statements
  • If I’ve left a cell (or row, in the case of the BBC) blank, that means it’s too hard for me to find or process or put into this structure

Looking at UK Arts & Culture funding

Introduction

This post is a branching off from my (George) personal blog, where I have been writing throughout lockdown about various things. I am interested to try to teach myself more about the Arts & Culture funding landscape in the UK, especially as the government has just announced their £1.57M grant, and because I’ve been trying harder to see where systemic racism and sexism live. I want to know how the funding will be distributed. I’m curious to see if I can draw the overall arts and culture funding picture a bit more clearly for myself, and thought others might be interested.

I would love for this to a be a conversation, especially if I’m really missing very important aspects as I explore. Comments are welcome.

Assets vs Need?

Today I haven’t been able to stop thinking of something that struck me when I first moved to the UK in 2014. One day, fairly soon after I’d moved here, I happened to have a coffee with Ed Vaizey, with my friend Wolfgang. He was very pleasant. I was not at all prepared as well as I should have been, and nothing came of it, which is one of my few regrets. But, the thing I noticed and remember most was that Mr. Vaizey’s shirt collar was frayed. How strange, I thought, that the Minster for Digital and Creative Industries couldn’t afford a shirt that wasn’t frayed. I mean, he has his own coat of arms.

Ed Vaizey’s coat of arms

I remember mentioning this to a new English friend who informed me that this was an ever so subtle class marker. That upper class people like to wear things out instead of buying new replacements. Very, very wealthy people apparently don’t have much actual cash, since all their wealth is tied up in things that are difficult to extract their wealth from, like a big house, or, say, most of the real estate in Bloomsbury, as is the case with the British Museum, whose total net assets were listed as £1,001,693,000 in its 2018/19 Annual Report on the Consolidated Balance Sheet, as at 31 March 2019. How hard it must be to see all that money listed as a line item in a balance sheet and not be able to use it.

I’ve been thinking about that £1,570,000,000 cash injection offered by the government to the arts sector, and trying to think about Who Needs This Funding The Least? It’s early days for my data gathering and poking, and sadly, the decisions have likely already been made about who is going to benefit, although I understand there will be some form of application for some. I’ve found it easy to let the various giant numbers flying around wash over me… 1 billion here, 120 million there so step one is to try to see some of these numbers, and particularly to see them against other comparators, to get a sense of the scale of the situation.

Today I learned that the Department of Culture, Media and Sport (DCMS) gives funds each year to what’s called “Arm’s Length Bodies” which receive what’s called “Grant in Aid”. I found a DCMS Estimate Memorandum containing a certain Table 3: Comparing the Grant in Aid funding of our Arm’s length bodies in 2016-17 through to 2018-19, which I share with you below: 

Organisation2017 projected2017 actual2018 projected
British Broadcasting Corporation£3,156,700,000£3,185,400,000£3,255,500,000
Arts Council England£460,526,000£494,183,000£479,972,000
Ofcom1£72,295,000£123,039,000£106,300,000
Sport England£105,649,000£101,787,000£104,795,000
British Library£93,911,000£93,893,000£93,443,000
Historic England£87,806,000£87,912,000£90,734,000
UK Sport£53,536,000£60,890,000£61,431,000
VisitBritain£56,972,000£60,458,000£56,818,000
British Museum£53,569,000£53,473,000£42,046,000
Natural History Museum£49,115,000£41,815,000£41,815,000
Science Museum Group£43,343,000£46,903,000£40,428,000
Tate Gallery£40,251,000£38,066,000£37,566,000
Victoria & Albert Museum£40,257,000£37,726,000£37,176,000
National Gallery£24,092,000£24,092,000£24,092,000
Imperial War Museum£32,136,000£25,347,000£23,634,000
British Film Institute£23,965,000£23,587,000£20,878,000
National Museums Liverpool£20,050,000£19,761,000£19,761,000
Royal Museums Greenwich£16,019,000£16,019,000£15,869,000
S4C3£6,762,000£6,956,000£15,097,000
Royal Armouries£7,088,000£7,788,000£8,938,000
UKAD£6,096,000£6,046,000£7,998,000
National Portrait Gallery£6,637,000£9,734,000£6,634,000
National Heritage Memorial Fund£35,250,000£5,489,000£5,000,000
Horniman Museum and Gardens£4,549,000£4,320,000£3,820,000
Information Commissioners Office£3,790,000£5,740,000£3,750,000
The Wallace Collection£2,711,000£3,711,000£2,711,000
Churches Conservation Trust£2,749,000£2,738,000£2,604,000
Geffrye Museum£1,696,000£1,786,000£1,796,000
Sports Grounds Safety Authority 2£0£1,542,000£1,601,000
Sir John Soane’s£1,983,000£1,012,000£1,012,000
Table 3: Comparing the Grant in Aid funding of our Arm’s length bodies in 2016-17 through to 2018-19

Isn’t that interesting? That is a bunch of support. What robust affirmative action! A total of £4,613,219,000 projected to be granted to these 30 “arm’s length” organisations in 2018. There’s the British Museum up there in the list, which was projected to receive £42,046,000 in 2018. The BM’s annual report (linked above) confirms for us that indeed: “The British Museum received £39.4 million revenue and £13.1 million capital grant-in-aid from the DCMS in 2018/19” on page 16.

All 30 organisations who receive this Grant in Aid are required to sign a Management Agreement with DCMS, and report back in a standard way so DCMS can see how well the grants are being used and measure performance consistently. For example, here is the Total income of DCMS-funded cultural organisations 2018/19 report from DCMS.

Big numbers can be numbing

The government’s support package announced this week to be spread across lots more organisations is about 34.03% of that total annual “arms length” grant in aid dispensed in 2018. I hope my maths is correct, otherwise I’m going to look even more naive and foolish. I am very willing to be called out on this if I have made mistakes, so I can learn more. I have tried to not make mistakes. I found Will Gompertz’s analysis of the situation useful, and he notes the basic breakdown of the COVID arts and culture grant we know today:

The £1.15bn support pot for cultural organisations in England is made up of £880m in grants and £270m of repayable loans. The government said the loans would be “issued on generous terms”.

Funding will also go to the devolved administrations – £33m to Northern Ireland, £97m to Scotland and £59m to Wales.

A further £100m will be earmarked for national cultural institutions in England and the English Heritage Trust.

There will also be £120m to restart construction on cultural infrastructure and for heritage construction projects in England that were paused due to the pandemic.

The government said decisions on who will get the funding would be made “alongside expert independent figures from the sector”.

Coronavirus: Emergency money for culture ‘won’t save every job’ 7 July 2020

I am definitely glad to see that the cultural sector has been recognised as having value and need for support. This is unequivocally good. The very early point I am trying to make is that there might be a way to look past and around and through the giant nationals with the loudest voices and ongoing DCMS support in the millions and with vast assets (many of whom as speaking to us via that 5 July government press release to say how happy they are) to see if it’s possible, finally, to illuminate the smaller players, the dynamic and struggling groups, the covens of freelance talent, the support companies, and basically everyone else who isn’t one of the biggies.

Staring into the status quo

I chatted about this with a few arts-related friends, and Clare directed me to a report called The Art of Dying written in 2005 by John Knell. I hope everyone who’s dispensing funds has studied it and can recite it from start to finish. It’s a response to a conference held the year before, where these three main insights were born, and I quote:

1. That the portfolio of arts organisations in the UK has become too fixed

2. That there are too many undercapitalised arts organisations, operating at near breaking point organisationally and financially, whose main preoccupation is survival diverting their energies from the central mission of cultural creativity

3. That we need to provoke a more challenging public conversation about the infrastructure supporting the arts in the UK, and the strategy and modus operandi of arts organisation

The Art of Dying

I really like what Mr. Knell is writing in this paper – it’s definitely worth your time to read it. It’s important to be able to look at each other and agree that an organisation with £1,001,693,000 worth of assets is stable. Or bloody well should be.

So interesting. 

Chatting further with more arts and culture colleagues, I was encouraged — thanks, Fiona — to reframe the question to: Who Needs It The Most? This is a much harder question. I’d consider myself to be a true friend to all museums everywhere, but I have to admit I particularly love the small ones that are super fucked, and definitely don’t have £1,001,693,000 hiding away in real estate or other investments that are difficult to access because there’s some form of governance in the way of deciding to release them. 

As I look at the big, open, reported numbers, I will also be on the hunt for the numbers hiding in plain sight, or not documented at all. And please, if you can direct me to good reporting on arts and culture networks and their funding, I would absolutely love the steer.

New Work: MoMA Exhibition Spelunker

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.org.

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

Voila!   http://spelunker.moma.org

moma-screenshot-home

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.

moma-screenshot-exhibition-graph

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

moma-screenshot-department-map

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.

moma-screenshot-first-curators

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?

moma-screenshot-prolific-curators

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?

moma-screenshot-artists-top10

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…

cri_000000348940
Useful Objects of American Design under $10.00

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.

cri_000000350367.jpg
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.

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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?

moma-screenshot-pressrelease

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!

Internal R&D Project #4: Two Way Street

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.

chloe

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.

thing

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

facets

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

found

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.

Europeana Tech 2015 Closing Plenary

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.

Untitled

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.