From piles of material to patchwork: How do we embed the production of usable collections data into library work?

How do we embed the production of usable collections data into library work?These notes were prepared for a panel discussion at the ‘Always Already Computational: Collections as Data‘ (#AACdata) workshop, held in Santa Barbara in March 2017. While my latest thinking on the gap between the scale of collections and the quality of data about them is informed by my role in the Digital Scholarship team at the British Library, I’ve also drawn on work with catalogues and open cultural data at Melbourne Museum, the Museum of London, the Science Museum and various fellowships. My thanks to the organisers and the Institute of Museum and Library Services for the opportunity to attend. My position paper was called ‘From libraries as patchwork to datasets as assemblages?‘ but in hindsight, piles and patchwork of material seemed a better analogy.

The invitation to this panel asked us to share our experience and perspective on various themes. I’m focusing on the challenges in making collections available as data, based on years of working towards open cultural data from within various museums and libraries. I’ve condensed my thoughts about the challenges down into the question on the slide: How do we embed the production of usable collections data into library work?

It has to be usable, because if it’s not then why are we doing it? It has to be embedded because data in one-off projects gets isolated and stale. ‘Production’ is there because infrastructure and workflow is unsexy but necessary for access to the material that makes digital scholarship possible.

One of the biggest issues the British Library (BL) faces is scale. The BL’s collections are vast – maybe 200 million items – and extremely varied. My experience shows that publishing datasets (or sharing them with aggregators) exposes the shortcomings of past cataloguing practices, making the size of the backlog all too apparent.

Good collections data (or metadata, depending on how you look at it) is necessary to avoid the overwhelmed, jumble sale feeling of using a huge aggregator like Europeana, Trove, or the DPLA, where you feel there’s treasure within reach, if only you could find it. Publishing collections online often increases the number of enquiries about them – how can institution deal with enquiries at scale when they already have a cataloguing backlog? Computational methods like entity identification and extraction could complement the ‘gold standard’ cataloguing already in progress. If they’re made widely available, these other methods might help bridge the resourcing gaps that mean it’s easier to find items from richer institutions and countries than from poorer ones.

Photo of piles of materialYou probably already all know this, but it’s worth remembering: our collections aren’t even (yet) a patchwork of materials. The collections we hold, and the subset we can digitise and make available for re-use are only a tiny proportion of what once existed. Each piece was once part of something bigger, and what we have now has been shaped by cumulative practical and intellectual decisions made over decades or centuries. Digitisation projects range from tiny specialist databases to huge commercial genealogy deals, while some areas of the collections don’t yet have digital catalogue records. Some items can’t be digitised because they’re too big, small or fragile for scanning or photography; others can’t be shared because of copyright, data protection or cultural sensitivities. We need to be careful in how we label datasets so that the absences are evident.

(Here, ‘data’ may include various types of metadata, automatically generated OCR or handwritten text recognition transcripts, digital images, audio or video files, crowdsourced enhancements or any combination or these and more)

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In addition to the incompleteness or fuzziness of catalogue data, when collections appear as data, it’s often as great big lumps of things. It’s hard for normal scholars to process (or just unzip) 4gb of data.

Currently, datasets are often created outside normal processes, and over time they become ‘stale’ as they’re not updated when source collections records change. And when they manage to unzip them, the records rely on internal references – name authorities for people, places, etc – that can only be seen as strings rather than things until extra work is undertaken.

The BL’s metadata team have experimented with ‘researcher format’ CSV exports around specific themes (eg an exhibition), and CSV is undoubtedly the most accessible format – but what we really need is the ability for people to create their own queries across catalogues, and create their own datasets from the results. (And by queries I don’t mean SPARQL but rather faceted browsing or structured search forms).

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Collections are huge (and resources relatively small) so we need to supplement manual cataloguing with other methods. Sometimes the work of crafting links from catalogues to external authorities and identifiers will be a machine job, with pieces sewn together at industrial speed via entity recognition tools that can pull categories out or text and images. Sometimes it’s operated by a technologist who runs records through OpenRefine to find links to name authorities or Wikidata records. Sometimes it’s a labour of scholarly love, with links painstakingly researched, hand-tacked together to make sure they fit before they’re finally recorded in a bespoke database.

This linking work often happens outside the institution, so how can we ingest and re-use it appropriately? And if we’re to take advantage of computational methods and external enhancements, then we need ways to signal which categories were applied by catalogues, which by software, by external groups, etc.

The workflow and interface adjustments required would be significant, but even more challenging would be the internal conversations and changes required before a consensus on the best way to combine the work of cataloguers and computers could emerge.

The trick is to move from a collection of pieces to pieces of a collection. Every collection item was created in and about places, and produced by and about people. They have creative, cultural, scientific and intellectual properties. There’s a web of connections from each item that should be represented when they appear in datasets. These connections help make datasets more usable, turning strings of text into references to things and concepts to aid discoverability and the application of computational methods by scholars. This enables structured search across datasets – potentially linking an oral history interview with a scientist in the BL sound archive, their scientific publications in journals, annotated transcriptions of their field notebooks from a crowdsourcing project, and published biography in the legal deposit library.

A lot of this work has been done as authority files like AAT, ULAN etc are applied in cataloguing, so our attention should turn to turning local references into URIs and making the most of that investment.

Applying identifiers is hard – it takes expert care to disambiguate personal names, places, concepts, even with all the hinting that context-aware systems might be able to provide as machine learning etc techniques get better. Catalogues can’t easily record possible attributions, and there’s understandable reluctance to publish an imperfect record, so progress on the backlog is slow. If we’re not to be held back by the need for records to be perfectly complete before they’re published, then we need to design systems capable of capturing the ambiguity, fuzziness and inherent messiness of historical collections and allowing qualified descriptors for possible links to people, places etc. Then we need to explain the difference to users, so that they don’t overly rely on our descriptions, making assumptions about the presence or absence of information when it’s not appropriate.

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Photo of pipes over a buildingA lot of what we need relies on more responsive infrastructure for workflows and cataloguing systems. For example, the BL’s systems are designed around the ‘deliverable unit’ – the printed or bound volume, the archive box – because for centuries the reading room was where you accessed items. We now need infrastructure that makes items addressable at the manuscript, page and image level in order to make the most of the annotations and links created to shared identifiers.

(I’d love to see absorbent workflows, soaking up any related data or digital surrogates that pass through an organisation, no matter which system they reside in or originate from. We aren’t yet making the most of OCRd text, let alone enhanced data from other processes, to aid discoverability or produce datasets from collections.)

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My final thought – we can start small and iterate, which is just as well, because we need to work on understanding what users of collections data need and how they want to use them. We’re making a start and there’s a lot of thoughtful work behind the scenes, but maybe a bit more investment is needed from research libraries to become as comfortable with data users as they are with the readers who pass through their physical doors.

Three ways you can help with ‘In their own words: collecting experiences of the First World War’ (and a CENDARI project update)

Somehow it’s a month since I posted about my CENDARI research project (in Moving forward: modelling and indexing WWI battalions) on this site. That probably reflects the rhythm of the project – less trying to work out what I want to do and more getting on with doing it. A draft post I started last month simply said, ‘A lot of battalions were involved in World War One’. I’ll do a retrospective post soon, and here’s a quick summary of on-going work.

First, a quick recap. My project has two goals – one, to collect a personal narrative for each battalion in the Allied armies of the First World War; two, to create a service that would allow someone to ask ‘where was a specific battalion at a specific time?’. Together, they help address a common situation for people new to WWI history who might ask something like ‘I know my great-uncle was in the 27th Australian battalion in March 1916, where would he have been and what would he have experienced?’.

I’ve been working on streamlining and simplifying the public-facing task of collecting a personal narrative for each battalion, and have written a blog post, Help collect soldiers’ experiences of WWI in their own words, that reduces it to three steps:

  1. Take one of the diaries, letters and memoirs listed on the Collaborative Collections wiki, and
  2. Match its author with a specific regiment or battalion.
  3. Send in the results via this form.

If you know of a local history society, family historian or anyone else who might be interested in helping, please send them along to this post: Help collect soldiers’ experiences of WWI in their own words.

Work on specifying the relevant data structures to support a look-up service to answer questions about a specific units location and activities at a specific time largely moved to the wiki:

You can see the infobox structures in progress by flipping from the talk to the Template tabs. You’ll need to request an account to join in but more views, sample data and edge cases would be really welcome.

Populating the list of battalions and other units has been a huge task in itself, partly because very few cultural institutions have definitive lists of units they can (or want to) share, but it’s necessary to support both core goals. I’ve been fortunate to have help (see ‘Thanks and recent contributions’ on ‘How you can help‘) but the task is on-going so get in touch if you can help!

So there are three different ways you can help with ‘In their own words: collecting experiences of the First World War’:

Finally, last week I was in New Zealand to give a keynote on this work at the National Digital Forum. The video for ‘Collaborative collections through a participatory commons‘ is online, so you can catch up on the background for my project if you’ve got 40 minutes or so to spare. Should you be in Dublin, I’m giving a talk on ‘A pilot with public participation in historical research: linking lived experiences of the First World War’ at the Trinity Long Room Hub today (thus the poster).

And if you’ve made it this far, perhaps you’d like to apply for a CENDARI Visiting Research Fellowships 2015 yourself?

Moving forward: modelling and indexing WWI battalions

A super-quick update from my CENDARI Fellowship this week. I set up the wiki for In their own words: linking lived experiences of the First World War a week ago but only got stuck into populating it with lists of various national battalions this week. My current task list, copied from the front page is to:

If you can help with any of that, let me know! Or just get stuck in and edit the site.
I’ve started another Google Doc with very sketchy Notes towards modelling information about World War One Battalions. I need to test it with more battalion histories and update it iteratively. At this stage my thinking is to turn it into an InfoBox format to create structured data via the wiki. It’s all very lo-fi and much less designed than my usual projects, but I’m hoping people will be able to help regardless.
So, in this phase of the project, the aim is find a personal narrative – a diary, letters, memoirs or images – for each military unit in the British Army. Can you help? 

In which I am awed by the generosity of others, and have some worthy goals

Grand Canal Dock at night, DublinA quick update from my CENDARI fellowship working on a project that’s becoming ‘In their own words: linking lived experiences of the First World War‘. I’ve spent the week reading (again a mixture of original diaries and letters, technical stuff like ontology documentation and also WWI history forums and ‘amateur’ sites) and writing. I put together a document outlining a rang of possible goals and some very sketchy tech specs, and opened it up for feedback. The goals I set out are copied below for those who don’t want to delve into detail. The commentable document, ‘Linking lived experiences of the First World War’: possible goals and a bunch of technical questions goes into more detail.

However, the main point of this post is to publicly thank those who’ve helped by commenting and sharing on the doc, on twitter or via email. Hopefully I’m not forgetting anyone, as I’ve been blown away by and am incredibly grateful for the generosity of those who’ve taken the time to at least skim 1600 words (!). It’s all helped me clarify my ideas and find solutions I’m able to start implementing next week. In no order at all – at CENDARI, Jennifer Edmond, Alex O’Connor, David Stuart, Benjamin Štular, Francesca Morselli, Deirdre Byrne; online Andrew Gray @generalising; Alex Stinson @ DHKState; jason webber @jasonmarkwebber; Alastair Dunning @alastairdunning; Ben Brumfield @benwbrum; Christine Pittsley; Owen Stephens @ostephens; David Haskiya @DavidHaskiya; Jeremy Ottevanger @jottevanger; Monika Lechner @lemondesign; Gavin Robinson ‏@merozcursed; Tom Pert @trompet2 – thank you all!

Worthy goals (i.e. things I’m hoping to accomplish, with the help of historians and the public; only some of which I’ll manage in the time)

At the end of this project, someone who wants to research a soldier in WWI but doesn’t know a thing about how armies were structured should be able to find a personal narrative from a soldier in the same bit of the army, to help them understand experiences of the Great War.

Hopefully these personal accounts will provide some context, in their own words, for the lived experiences of WWI. Some goals listed are behind-the-scenes stuff that should just invisibly make personal diaries, letters and memoirs more easily discoverable. It needs datasets that provide structures that support relationships between people and documents; participatory interfaces for creating or enhancing information about contemporary materials (which feed into those supporting structures), and interfaces that use the data created.

More specifically, my goals include:

    • A personal account by someone in each unit linked to that unit’s record, so that anyone researching a WWI name would have at least one account to read. To populate this dataset, personal accounts (diaries, letters, etc) would need to be linked to specific soldiers, who can then be linked to specific units. Linking published accounts such as official unit histories would be a bonus. [Semantic MediaWiki]
    • Researched links between individual men and the units they served in, to allow their personal accounts to be linked to the relevant military unit. I’m hoping I can find historians willing to help with the process of finding and confirming the military unit the writer was in. [Semantic MediaWiki]
    • A platform for crowdsourcing the transcription and annotation of digitised documents. The catch is that the documents for transcription would be held remotely on a range of large and small sites, from Europeana’s collection to library sites that contain just one or two digitised diaries. Documents could be tagged/annotated with the names of people, places, events, or concepts represented in them. [Semantic MediaWiki??]
    • A structured dataset populated with the military hierarchy (probably based on The British order of battle of 1914-1918) that records the start and end dates of each parent-child relationship (an example of how much units moved within the hierarchy)
    • A published webpage for each unit, to hold those links to official and personal documents about that unit in WWI. In future this page could include maps, timelines and other visualisations tailored to the attributes of a unit, possibly including theatres of war, events, campaigns, battles, number of privates and officers, etc. (Possibly related to CENDARI Work Package 9?) [Semantic MediaWiki]
    • A better understanding of what people want to know at different stages of researching WWI histories. This might include formal data gathering, possibly a combination of interviews, forum discussions or survey


Goals that are more likely to drop off, or become quick experiments to see how far you can get with accessible tools:
    • Trained ‘named entity recognition’ and ‘natural language processing’ tools that could be run over transcribed text to suggest possible people, places, events, concepts, etc [this might drop off the list as the CENDARI project is working on a tool called Pineapple (PDF poster). That said, I’ll probably still experiment with the Stanford NER tool to see what the results are like]
    • A way of presenting possible matches from the text tools above for verification or correction by researchers. Ideally, this would be tied in with the ability to annotate documents
    • The ability to search across different repositories for a particular soldier, to help with the above.


Linking lived experiences of WWI through battalions?

Another update from my CENDARI Fellowship at Trinity College Dublin, looking at ‘In their own words: linking lived experiences of the First World War’, which is a small-scale, short-term pilot based on WWI collections. My first post is Defining the scope: week one as a CENDARI Fellow. Over the past two weeks I’ve done a lot of reading – more WWI diaries and letters; WWI histories and historiography; specialist information like military structures (orders of battle, etc). I’ve also sketched out lots of snippets of possible functions, data, relationships and other outcomes.

I’ve narrowed the key goal (or minimum viable product, if you prefer) of my project to linking personal accounts of the war – letters, diaries, memoirs, photographs, etc – to battalions, by creating links from the individual who wrote them to their military unit. Once these personal accounts are linked to particular military units, they can be linked to higher units – from the battalion, ship or regiment to brigade, corps, etc – and to particular places, activities, events and campaigns. The idea behind this is to provide context for an individual’s experience of WWI by linking to narratives written by people in the same situation. I’m still working out how to organise the research process of matching the right soldier to the right battalion/regiment/ship so that relevant personal stories are discoverable. I’m also still working out which attributes of a battalion are relevant, how granular the data will be, and how to design for the inevitable variation in data quality (for example, the availability of records for different armies varies hugely). Finally, I’m still working out which bits need computer science tools and which need the help of other historians.

Given the number of centenary projects, I was hoping to find more structured data about WWI entities. Trenches to Triples would be useful source of permanent URLs, and terms to train named entity recognition, but am I missing other sources?

There’s a lot of content, and so much activity around WWI records, but it’s spread out across the internet. Individual people and small organisations are digitising and transcribing diaries and letters. Big collecting projects like Europeana have lots of personal accounts, but they’re often not transcribed and they don’t seem to be linked to structured data about the item itself. Some people have painstakingly transcribed unit diaries, but they’re not linked from the official site, so others wouldn’t know there’s a more easily read version of the diary available. I’ve been wondering if you could crowdsource the process of transcribing records held elsewhere, and offer the transcripts back to sites. Using dedicated transcription software would let others suggest corrections, and might also make it possible to link sections of the text to external ‘entities’ like names, places, events and concepts.

Albert Henry Bailey. Image:
Sir George Grey Special Collections,
Auckland Libraries, AWNS-19150909-39-5

To help figure out the issues researchers face and the variations in available resources, I’m researching randomly selected soldiers from different Allied forces. I’ve posted my notes on Private Albert Henry Bailey, service number 13/970a. You’ll see that they’re in prose form, and don’t contain any structured data. Most of my research used digitised-but-not-transcribed images of documents, with some transcribed accounts. It would definitely benefit from deeper knowledge of military history – for a start, which battalions were in the same place as his unit at the same time?

This account of the arrival and first weeks of the Auckland Mount Rifles at Gallipoli from the official unit history gives a sense of the density and specificity of local place names, as does the official unit diary, and I assume many personal accounts. I’m not sure how named entity recognition tools will cope, and ideally I’d like to find lists of places to ‘train’ the tools (including possibly some from the ‘Trenches to Triples’ project).

If there aren’t already any structured data sources for military hierarchies in WWI, do I have to make one? And if so, how? The idea would be to turn prose descriptions like this Australian War Memorial history of the 27th AIF Battalion, this order of battle of the 2nd Australian Division and any other suitable sources into structured data. I can see some ways it might be possible to crowdsource the task, but it’s a big task. But it’s worth it – providing a service that lets people look up which higher military units, places. activities and campaigns a particular battalion/regiment/ship was linked to at a given time would be a good legacy for my research.

I’m sure I’m forgetting lots of things, and my list of questions is longer than my list of answers, but I should end here. To close, I want to share a quote from the official history of the Auckland Mounted Rifles. The author said he ‘would like to speak of the splendid men of the rank and file who died during this three months’ struggle. Many names rush to the memory, but it is not possible to mention some without doing an injustice to the memory of others’. I guess my project is driven by a vision of doing justice to the memory of every soldier, particularly those ordinary men who aren’t as easily found in the records. I’m hoping that drawing on the work of other historians and re-linking disparate sources will help provide as much context as possible for their experiences of the First World War.

Update, 15 October 2014: if you’ve made it this far, you might also be interested in chipping in at ‘Linking lived experiences of the First World War’: possible goals and a bunch of technical questions.

Defining the scope: week one as a CENDARI Fellow

I’m coming to the end of my first week as a Transnational Access Fellow with the CENDARI project at the Trinity College Dublin Long Room Hub. CENDARI ‘aims to leverage innovative technologies to provide historians with the tools by which to contextualise, customise and share their research’, which dovetails with my PhD research incredibly well. This Fellowship gives me an opportunity to extend my ideas about ‘Enriching cultural heritage collections through a Participatory Commons‘ without trying to squish them into a history thesis, and is probably perfectly timed in giving me a break from writing up.

View over Trinity College Dublin

There are two parts to my CENDARI project ‘Bridging collections with a participatory Commons: a pilot with World War One archives’. The first involves working on the technical, data and cultural context/requirements for the ‘participatory history commons’ as an infrastructure; the second is a demonstrator based on that infrastructure. I’ll be working out how official records and ‘shoebox archives’ can be mined and indexed to help provide what I’m calling ‘computationally-generated context’ for people researching lives touched by World War One.

This week I’ve read metadata schema (MODS extended with TEI and a local schema, if you’re interested) and ontology guidelines, attended some lively seminars on Irish history, gotten my head around CENDARI’s work packages and the structure of the British army during WWI. I’ve started a list of nearby local history societies with active research projects to see if I can find some working on WWI history – I’d love to work with people who have sources they want to digitise and generally do more with, and people who are actively doing research on First World War lives. I’ve started to read sample primary materials and collect machine-readable sources so I can test out approaches by manually marking-up and linking different repositories of records. I’m going to spend the rest of the day tidying up my list of outcomes and deliverables and sketching out how all the different aspects of my project fit together. And tonight I’m going to check out some of the events at Discover Research Dublin. Nerd joy!

‘The cooperative archive’?

Finally, I’ve dealt with something I’d put off for ages. ‘Commons’ is one of those tricky words that’s less resonant than it could be, so I looked for a better name than the ‘participatory history commons’. because ‘commons’ is one of those tricky words that’s less resonant than it could be. I doodled around words like collation, congeries, cluster, demos, assemblage, sources, commons, active, engaged, participatory, opus, archive, digital, posse, mob, cahoots and phrases like collaborative collections, collaborative history, history cooperative, but eventually settled on ‘cooperative archive’. This appeals because ‘cooperative’ encompasses attitudes or values around working together for a common purpose, and it includes those who share records and those who actively work to enhance and contextualise them. ‘Archive’ suggests primary sources, and can be applied to informal collections of ‘shoebox archives’ and the official holdings of museums, libraries and archives.

What do you think – does ‘cooperative archive’ work for you? Does your first reaction to the name evoke anything like my thoughts above?

Update, October 11: following some market testing on Facebook, it seems ‘collaborative collections’ best describes my vision.

Sharing is caring keynote ‘Enriching cultural heritage collections through a Participatory Commons’

Enriching cultural heritage collections through a Participatory Commons platform: a provocation about collaborating with users

Mia Ridge, Open University Contact me: @mia_out or

[I was invited to Copenhagen to talk about my research on crowdsourcing in cultural heritage at the 3rd international Sharing is Caring seminar on April 1. I’m sharing my notes in advance to make life easier for those awesome people following along in a second or third language, particularly since I’m delivering my talk via video.]

Today I’d like to present both a proposal for something called the ‘Participatory Commons’, and a provocation (or conversation starter): there’s a paradox in our hopes for deeper audience engagement through crowdsourcing: projects that don’t grow with their participants will lose them as they develop new skills and interests and move on. This talk presents some options for dealing with this paradox and suggests a Participatory Commons provides a way to take a sector-wide view of active engagement with heritage content and redefine our sense of what it means when everybody wins.

I’d love to hear your thoughts about this – I’ll be following the hashtag during the session and my contact details are above.

Before diving in, I wanted to reflect on some lessons from my work in museums on public engagement and participation.

My philosophy for crowdsourcing in cultural heritage (aka what I’ve learnt from making crowdsourcing games)

One thing I learnt over the past years: museums can be intimidating places. When we ask for help with things like tagging or describing our collections, people want to help but they worry about getting it wrong and looking stupid or about harming the museum.

The best technology in the world won’t solve a single problem unless it’s empathically designed and accompanied by social solutions. This isn’t a talk about technology, it’s a talk about people – what they want, what they’re afraid of, how we can overcome all that to collaborate and work together.

Dora’s Lost Data

So a few years ago I explored the potential of crowdsourcing games to make helping a museum less scary and more fun. In this game, ‘Dora’s Lost Data‘, players meet a junior curator who asks them to tag objects so they’ll be findable in Google. Games aren’t the answer to everything, but identifying barriers to participation is always important. You have to understand your audiences – their motivations for starting and continuing to participate; the fears, anxieties, uncertainties that prevent them participating. [My games were hacked together outside of work hours, more information is available at My MSc dissertation: crowdsourcing games for museums; if you’d like to see properly polished metadata games check out Tiltfactor’s]

Mutual wins – everybody’s happy

My definition of crowdsourcing: cultural heritage crowdsourcing projects ask the public to undertake tasks that cannot be done automatically, in an environment where the activities, goals (or both) provide inherent rewards for participation, and where their participation contributes to a shared, significant goal or research area.

It helps to think of crowdsourcing in cultural heritage as a form of volunteering. Participation has to be rewarding for everyone involved. That sounds simple, but focusing on the audiences’ needs can be difficult when there are so many organisational needs competing for priority and limited resources for polishing the user experience. Further, as many projects discover, participant needs change over time…

What is a Participatory Commons and why would we want one?

First, I have to introduce you to some people. These are composite stories (personas) based on my research…

Two archival historians, Simone and Andre. Simone travels to archives in her semester breaks to stock up on research material, taking photos of most documents ‘in case they’re useful later’, transcribing key text from others. Andre is often at the next table, also looking for material for his research. The documents he collected for his last research project would be useful for Simone’s current book but they’ve never met and he has no way of sharing that part of his ‘personal research collection’ with her. Currently, each of these highly skilled researchers take their cumulative knowledge away with them at the end of the day, leaving no trace of their work in the archive itself. Next…

Two people from a nearby village, Martha and Bob. They joined their local history society when they retired and moved to the village. They’re helping find out what happened to children from the village school’s class of 1898 in the lead-up to and during World War I. They are using census returns and other online documents to add records to a database the society’s secretary set up in Excel. Meanwhile…

A family historian, Daniel. He has a classic ‘shoebox archive’ – a box containing his grandmother Sarah’s letters and diary, describing her travels and everyday life at the turn of the century. He’s transcribing them and wants to put them online to share with his extended family. One day he wants to make a map for his kids that shows all the places their great-grandmother lived and visited. Finally, there’s…

Crowdsourcer Nisha.She has two young kids and works for a local authority. She enjoys playing games like Candy Crush on her mobile, and after the kids have gone to bed she transcribes ship logs on the Old Weather website while watching TV with her husband. She finds it relaxing, feels good about contributing to science and enjoys the glimpses of life at sea. Sites like Old Weather use ‘microtasks’ – tiny, easily accomplished tasks – and crowdsourcing to digitise large amounts of text.

Helping each other?

None of our friends above know it, but they’re all looking at material from roughly the same time and place. Andre and Simone could help each other by sharing the documents they’ve collected over the years. Sarah’s diaries include the names of many children from her village that would help Martha and Bob’s project, and Nisha could help everyone if she transcribed sections of Sarah’s diary.

Connecting everyone’s efforts for the greater good: Participatory Commons

This image shows the two main aspects of the Participatory Commons: the different sources for content, and the activities that people can do with that content.

The Participatory Commons (image: Mia Ridge)

The Participatory Commons is a platform where content from different sources can be aggregated. Access to shared resources underlies the idea of the ‘Commons’, particularly material that is not currently suitable for sites like Europeana, like ‘shoebox archives’ and historians’ personal record collections. So if the ‘Commons’ part refers to shared resources, how is it participatory?

The Participatory Commons interface supports a range of activities, from the types of tasks historians typically do, like assessing and contextualising documents, activities that specialists or the public can do like identifying particular people, places, events or things in sources, or typical crowdsourcing tasks like fulltext transcription or structured tagging.

By combining the energy of crowdsourcing with the knowledge historians create on a platform that can store or link to primary sources from museums, libraries and archives with ‘shoebox archives’, the Commons could help make our shared heritage more accessible to all. As a platform that makes material about ordinary people available alongside official archives and as an interface for enjoyable, meaningful participation in heritage work, the Commons could be a basis for ‘open source history’, redressing some of the absences in official archives while improving the quality of all records.

As a work in progress, this idea of the Participatory Heritage Commons has two roles: an academic thought experiment to frame my research, and as a provocation for GLAMs (galleries, museums, libraries, archives) to think outside their individual walls. As a vision for ‘open source history’, it’s inspired by community archives, public history, participant digitisation and history from below… This combination of a large underlying repository and more intimate interfaces could be quite powerful. Capturing some of the knowledge generated when scholars access collections would benefit both archives and other researchers.

‘Niche projects’ can be built on a Participatory Commons

As a platform for crowdsourcing, the Participatory Commons provides efficiencies of scale in the backend work for verifying and validating contributions, managing user accounts, forums, etc. But that doesn’t mean that each user would experience the same front-end interface.

Niche projects build on the Participatory Commons
(quick and dirty image: Mia Ridge)

My research so far suggests that tightly-focused projects are better able to motivate participants and create a sense of community. These ‘niche’ projects may be related to a particular location, period or topic, or to a particular type of material. The success of the New York Public Library’s What’s on the Menu project, designed around a collection of historic menus, and the British Library’s GeoReferencer project, designed around their historic map collection, both demonstrate the value of defining projects around niche topics.

The best crowdsourcing projects use carefully designed interactions tailored to the specific content, audience and data requirements of a given project. These interactions are usually For example, the Zooniverse body of projects use much of the same underlying software but projects are designed around specific tasks on specific types of material, whether classifying simple galaxy types, plankton or animals on the Serengeti, or transcribing ship logs or military diaries.

The Participatory Commons is not only a collection of content, it also allows ‘niche’ projects to be layered on top, presenting more focused sets of content, and specialist interfaces designed around the content, audience and purpose.


But there are still many barriers to consider, including copyright and technical issues and important cultural issues around authority, reliability, trust, academic credit and authorship. [There’s more background on this at my earlier post on historians and the Participatory Commons and Early PhD findings: Exploring historians’ resistance to crowdsourced resources.]

Now I want to set the idea of the Participatory Commons aside for a moment, and return to crowdsourcing in cultural heritage. I’ve been looking for factors in the success or otherwise of crowdsourcing projects, from grassroots, community-lead projects to big glamorous institutionally-lead sites.

I mentioned that Nisha found transcribing text relaxing. Like many people who start transcribing text, she found herself getting interested in the events, people and places mentioned in the text. Forums or other methods for participants to discuss their questions seem to help keep participants motivated, and they also provide somewhere for a spark of curiosity to grow (as in this forum post). We know that some people on crowdsourcing projects like Old Weather get interested in history, and even start their own research projects.

Crowdsourcing as gateway to further activity

You can see that happening on other crowdsourcing projects too. For example, Herbaria@Homeaims to document historical herbarium collections within museums based on photographs of specimen cards. So far participants have documented over 130,000 historic specimens. In the process, some participants also found themselves being interested in the people whose specimens they were documenting.

As a result, the project has expanded to include biographies of the original specimen collectors. It was able to accommodate this new interest through a project wiki, which has a combination of free text and structured data linking records between the transcribed specimen cards and individual biographies.

‘Levels of Engagement’ in citizen science

There’s a consistent enough pattern in science crowdsourcing projects that there’s a model from ‘citizen science’ that outlines different stages participants can move through, from undertaking simple tasks, joining in community discussion, through to ‘working independently on self-identified research projects’.[1]

Is this ‘mission accomplished’?

This is Nick Poole’s word cloud based on 40 museum missionstatements. With words like ‘enjoyment’, ‘access’, ‘learning’ appearing in museum missions, doesn’t this mean that turning transcribers into citizen historians while digitising and enhancing collections is a success? Well, yes, but…

Paths diverge; paradox ahead?

There’s a tension between GLAM’s desire to invite people to ‘go deeper’, to find their own research interests, to begin to become citizen historians; and the desire to ask people to help us with tasks set by GLAMs to help their work. Heritage organisations can try to channel that impulse to start research into questions about their own collections, but sometimes it feels like we’re asking people to do our homework for us. The scaffolds put in place to help make tasks easier may start to feel like a constraint.

Who has agency?

If people move beyond simple tasks into more complex tasks that require a greater investment of time and learning, then issues of agency – participants’ ability to make choices about what they’re working on and why – start to become more important. Would Wikipedia have succeeded if it dictated what contributors had to write about? We shouldn’t mistake volunteers for a workforce just because they can be impressively dedicated contributors.

Participatory project models

Turning again to citizen science – this time public participation in science research, we have a model for participatory projects according to the amount of control participants have over the design of the project itself – or to look at it another way, how much authority the organisation has ceded to the crowd. This model contains three categories: ‘contributory’, where the public contributes data to a project designed by the organisation; ‘collaborative’, where the public can help refine project design and analyse data in a project lead by the organisation; and ‘co-creative’, where the public can take part in all or nearly all processes, and all parties design the project together.[2]

As you can imagine, truly co-creative projects are rare. It seems cultural organisations find it hard to truly collaborate with members of the public; for many understandable reasons. The level of transparency required, and the investment of time for negotiating mutual interests, goals and capabilities increase as collaboration deepens. Institutional constraints and lack of time to engage in deep dialogue with participants make it difficult to find shared goals that work for all parties. It seems GLAMs sometimes try to take shortcuts and end up making decisions for the group, which means their ‘co-creative’ project is actually more just ‘collaborative’.

New challenges

When participants start to out-grow the tasks that originally got them hooked, projects face a choice. Some projects are experimenting with setting challenges for participants. Here you see ‘mysteries’ set by the UK’s Museum of Design in Plastics, and by San FranciscoPublic Library on History Pin. Finding the right match between the challenge set and the object can be difficult without some existing knowledge of the collection, and it can require a lot of on-going time to encourage participants. Putting the mystery under the nose of the person who has the knowledge or skills to solve it is another challenge that projects like this will have to tackle.

Working with existing communities of interest is a good start, but it also takes work to figure out where they hang out online (or in-person) and understand how they prefer to work. GLAMs sometimes fall into the trap of choosing the technology first, or trying something because it’s trendy; it’s better to start with the intersection between your content and the preferences of potential audiences.

But is it wishful thinking to hope that others will be interested in answering the questions GLAMs are asking?

A tension?

Should projects accept that some people will move on as they develop new interests, and concentrate on recruiting new participants to replace them? Do they try to find more interesting tasks or new responsibilities for participants, such as helping moderate discussions, or checking and validating other people’s work? Or should they find ways for the project grow as participants’ skill and knowledge increase? It’s important to make these decisions mindfully as the default is otherwise to accept a level of turnover as participants move on.

To return to lessons from citizen science, possible areas for deeper involvement include choosing or defining questions for study, analysing or interpreting data and drawing conclusions, discussing results and asking new questions.[3]However, heritage organisations might have to accept that the questions people want to ask might not involve their collections, and that these citizen historians’ new interests might not leave time for their previous crowdsourcing tasks.

Why is a critical mass of content in a Participatory Commons useful?

And now we return to the Participatory Commons and the question of why a critical mass of content would be useful.

Increasingly, the old divisions between museum, library and archive collections don’t make sense. For most people, content is content, and they don’t understand why a pamphlet about a village fete in 1898 would be described and accessed differently depending on whether it had ended up in a museum, library or archive catalogue.

Basing niche projects on a wider range of content creates opportunities for different types of tasks and levels of responsibility. Projects that provide a variety of tasks and roles can support a range of different levels and types of participant skills, availability, knowledge and experience.

A critical mass of material is also important for the discoverability of heritage content. Even the most sophisticated researcher turns to Google sometimes, and if your content doesn’t come up in the first few results, many researchers will never know it exists. It’s easy to say but less easy to make a reality: the easier it is to find your collections, the more likely it is that researchers will use them.

Commons as party?

More importantly, a critical mass of content in a Commons allows us to re-define ‘winning’. If participation is narrowly defined as belonging to individual GLAMs, when a citizen historian moves onto a project that doesn’t involve your collection then it can seem like you’ve lost a collaborator. But the people who developed a new research interest through a project at one museum might find they end up using records from the archive down the road, and transcribing or enhancing their records during their investigation. If all the institutions in the region shared their records on the Commons or let researchers take and share photos while using their collections, the researcher has a critical mass of content for their research and hopefully as a side-effect, their activities will improve links between collections. If the Commons allows GLAMs to take a sector-wide view then someone moving on to a different collection becomes a moment to celebrate, a form of graduation. In our wildest imagination, the Commons could be like a fabulous party where you never know what fabulous interesting people and things you’ll discover…

To conclude – by designing platforms that allow people to collect and improve records as they work, we’re helping everybody win.

Thank you! I’m looking forward to hearing your thoughts.

[1]M. Jordan Raddick et al., ‘Citizen Science: Status and Research Directions for the Coming Decade’, in astro2010: The Astronomy and Astrophysics Decadal Survey, vol. 2010, 2009,

[2]Rick Bonney et al., Public Participation in Scientific Research: Defining the Field and Assessing Its Potential for Informal Science Education. A CAISE Inquiry Group Report (Washington D.C.: Center for Advancement of Informal Science Education (CAISE), July 2009),

[3]Bonney et al., Public Participation in Scientific Research: Defining the Field and Assessing Its Potential for Informal Science Education. A CAISE Inquiry Group Report.

Image credits in order of appearance: Glider, Library of Congress, Great hall, Library of CongressCurzona Allport from Tasmanian Archive and Heritage Office, Hålanda Church, Västergötland, Sweden, Swedish National Heritage Board, Smithsonian Institution, Postmaster, General James A. Farley During National Air Mail Week, 1938Powerhouse Museum, Canterbury Bankstown Rugby League Football Club’s third annual Ball.

‘An (even briefer) history of open cultural data’ at GLAM-Wiki 2013

These are some of my notes for my invited plenary talk at GLAM-Wiki 2013 (Galleries, Libraries, Archives, Museums & Wikimedia, #GLAMWiki), held at the British Library on April 12-13, 2013. I don’t think I stuck that closely to them on the day, and in the interests of brevity I’ve left out the ‘timeline’ bits (but you can read about some of them in a related MuseumID article, ‘Where next for open cultural data in museums?‘) to focus on the lessons to be learnt from changes so far. There were lots of great talks and discussion at the event, you can view some of the presentations on Wikimedia UK’s YouTube channel.

A (now very) brief history of open cultural data

Firstly, thank you for the invitation to speak… This morning I want to highlight some key moments of change in the history of open cultural data – a history not only of licenses and data, but also of conversations, standards, and collaborations, of moments where things changed… I’ve included key moments from funders, legislative influences and the commercial sector too, as they create the context in which change happens and often have an effect on what’s considered possible. I’ll close by considering some of the lessons learnt.

[Please help improve this talk]

A caveat – there may well be a bias towards the English-speaking world (and to museums, because of my background). If you know of an open GLAM (gallery, library, archive, museum) data source I’ve missed, you can add it to the open cultural data/GLAM API wiki… or Lotte’s Belice‘s list of open culture milestones  timeline.


‘open cultural data’ is data from cultural institutions that is made available for use in a machine-readable format under an open licence. But each word in open, cultural, data is slightly more complicated so I’ll unpack them a little…


Office clerks, FNV. Voorlichting.

While the degree of openness required to be ‘open’ data can be contentious, at its simplest, ‘open’ refers to content that is available for use outside the institution that created it, whether for school homework projects, academic monographs or mobile phone apps. ‘Open’ may refer to licences that clarify the permissions and restrictions placed on data, or to the use of non-proprietary digital technologies, or ideally, to a combination of both open licences and technologies.

Ideally, open data is freely available for use and redistribution by anyone for any purpose, but in reality there are often restrictions. GLAMs may limit commercial use by licensing content for ‘non-commercial use only’, but as there is no clear definition of ‘non-commercial use’ in Creative Commons licences, some developers may choose not to risk using a dataset with an unclear licence. GLAMs may also release data for commercial use but still require attribution, either to help retain the provenance of the content, to help people find their way to related content or just because they’d like some credit for their work. GLAMs might also release data under custom licences that deal with their specific circumstances, but they are then difficult to integrate with content from other openly-licensed datasets.

Hybrid licensing models are a pragmatic solution for the current environment. They at least allow some use and may contribute to greater use of open cultural data while other issues are being worked out. For example, some institutions in the UK are making lower resolutions images available for re-use under an open licence while reserving high resolution versions for commercial sales and licensing. Or they may differentiate between scholarly and commercial use, or use more restrictive licences for commercially valuable images and release everything else openly.

I think this type of access is better than nothing, particularly if organisations can learn from the experience and release more data next time. Because these hybrid models are often experimental, their reception is important, and it’s helpful for GLAMs to be able to show they’ve had a positive impact and hopefully helped create relationships with groups like Wikipedia.


Cultural data is data about objects, publications (such as books, pamphlets, posters or musical scores), archival material, etc, created and distributed by museums, libraries, archives and other organisations.


It’s a useful distinction to discuss early with other cultural heritage staff as it’s easy to be talking at cross-purposes: data can refer to different types of content, from metadata or tombstone records (the basic titles, names, dates, places, materials, etc of a catalogue record), to entire collection records (including data such as researched and interpretive descriptions of objects, bibliographic data, related themes and narratives) to full digital surrogates of an object, document or book as images or transcribed text. Some organisations release open metadata, others release all their data including their images. If you can’t do open data (full content or ‘digital surrogates’ like photographs or texts) then at least open up the metadata (data about the content) as e.g. CC0 and the rest with another licence. Releasing data may involve licensing images, offering downloads from catalogue sites; ‘content donations’, APIs and machine-facing interfaces; term lists, etc. Much of the data that isn’t images isn’t immediately interesting, and may be designed for inter-collections interoperability or mashups rather than media commons.

Why is open cultural data important?

Before I go on, why do we care? Open cultural data is the foundation on which many projects can be built. It helps achieve organisational goals, mission; can help increase engagement with content; can create ‘network effect’ with related institutions; can be re-used by people who share your goals around access to knowledge and information – people like Wikipedians.

Some key moments in open cultural data

Events I discussed included the founding of Wikimedia, Europeana and Flickr Commons, previous GLAM-Wiki conferences, changes in licences for art images, library catalogue records and museum content, GLAM APIs and linked data services and the launch of the Digital Public Library of America next week.

Lessons learnt

Many of the changes are the results of years of conversation and collaboration – change is slow but it does happen. GLAMs work through slow iterations – try something, and if no-one dies, they’ll try something else. We are all ambassadors, and we are all translators, helping each domain understand the other.

Contradictory things GLAMs are told they must do

  • Give content away for the benefit of all
  • Monetise assets; protect against loss of potential income; protect against mis-use of collections; conserve collections in perpetuity; protect the IP of artists; demonstrate ROI on digitisation

It’s not easy for GLAMs to release all their data under an entirely open licence, but they don’t do it just to be annoying – it’s important to understand some of the pressures they’re under.  For example, GLAMs usually need to be able to track uses of their data and content to show the impact of digitising and publishing content, so they prefer attribution licences.

The issue of potential lost income – imaginary money that could be made one day if circumstances change, or profit that someone else makes off their opened data – is particularly difficult as hard to deal with [and here I ad-libbed, saying that it was like worrying about failing to meet the love of your life because you got on a different tube carriage – you can’t live your life chasing ghosts]. Ideally, open data needs to be understood as an input to the creative economy rather than an item on the balance sheet of an individual GLAM.

GLAMs worry about reputational damage, whether appearing on the front page of a tabloid newspaper for the ‘wrong’ reasons, questions being asked in Parliament, or critique from Wikipedians.  Over time, their mindset is changing from keeping ‘our data’ to being holders, custodians of our shared heritage.

Conversations, communities, collaborations

Conversations matter… we’re all working towards the same goal, but we have different types of anxieties and different problems we have to address.

GLAMs are about collections, knowledge, and audiences. Unlike most online work, they are used to seeing the excitement people experience walking through their door – help GLAMs understand what Wikipedians can do for different audiences by making those audience real to them. GLAMs are also used to being wined and dined before you lay the hard word on them. Just because you don’t need to ask for permission to use content doesn’t mean you shouldn’t start a conversation with an organisation. There are lots of people with similar goals inside organisations, so try to find them and work with them. Trust is a currency, don’t blow it!

Being truly collaborative sometimes means compromising (or picking your battles) and it definitely means practising empathy. Open data people could stop talking about open data as something you *do* to GLAMs, and GLAMs could stop thinking open data people just want to make your life difficult.

The role of higher powers

Government attitudes to open data make a big difference and they can also change the risks associated with publishing orphan works.  Governments can also help GLAMs open up their content by indemnifying them against the chance that someone else will monetise their data – consider it not a failure of the GLAM but a contribution to the creative and digital economy.

Things that are better than a poke in the eye with a sharp stick

  1. Kittens (and puppies)
  2. Cultural data that’s available online but isn’t (yet) openly licensed
  3. Cultural data online that is licensed for non-commercial use

Yes, the last two aren’t ideal, but they are great deal better than nothing.

Into the future…

GLAMs and Wikipedians may move at different paces, and may have different priorities and different ways of viewing the world, but we’re all working towards the same goals. Not everything is as open, but a lot more is open than it used to be. I sensed yesterday [the first day of the conference] that there are still some tensions between Wikimedians and GLAMers, moments when we need to take a deep breath and put empathy before a pithy put down, but I loved that Kat Walsh’s welcome yesterday described how Wikipedia used to focus on how different from others but now focuses on reaching out to others and figuring out how we’re the same.

GLAMs and Wikipedians have already used open cultural data to make the world a better place. Let’s celebrate the progress we’ve made and keep working on that…

GLAM-WIKI 2013 Friday attendees photograph by Mike Peel (

Congratulations to everyone who helped make it a great event, but particularly to Daria Cybulska and Andrew Gray (@generalising) for making everything work so smoothly, and Liam Wyatt (@wittylama) for the original invitation to speak.

Museums, Libraries, Archives and the Digital Humanities – get involved!

The short version: if you’ve got ideas on how museums, libraries and archives (i.e. GLAM) and the digital humanities can inspire and learn from each other, it’s your lucky day! Go add your ideas about concrete actions the Association for Computers and the Humanities can take to bring the two communities together or suggestions for a top ten ‘get started in museums and the digital humanities’ list (whether conference papers, journal articles, blogs or blog posts, videos, etc) to: ‘GLAM and Digital Humanities together FTW‘.

Update, August 23, 2012: the document is shaping up to be largely about ‘what can be done’ – which issues are shared by GLAMs and DH, how can we reach people in each field, what kinds of activities and conversations would be beneficial, how do we explain the core concepts and benefits of each field to the other? This suggests there’d be a useful second stage in focusing on filling in the detail around each of the issues and ideas raised in this initial creative phase. In the meantime, keep adding suggestions and sharing issues at the intersection of digital humanities and memory institutions.

A note on nomenclature: the genesis of this particular conversation was among museumy people so the original title of the document reflects that; it also reflects the desire to be practical and start with a field we knew well. The acronym GLAM (galleries, libraries, archives and museums) neatly covers the field of cultural heritage and the arts, but I’m never quite sure how effective it is as a recognisable call-to-action.  There’s also a lot we could learn from the field of public history, so if that’s you, consider yourself invited to the party!

The longer version: in an earlier post from July’s Digital Humanities conference in Hamburg I mentioned that a conversation over twitter about museums and digital humanities lead to a lunch with @ericdmj, @clairey_ross, @briancroxall, @amyeetx where we discussed simple ways to help digital humanists get a sense of what can be learnt from museums on topics like digital projects, audience outreach, education and public participation. It turns out the Digital Humanities community is also interested in working more closely with museums, as demonstrated by the votes for point 3 of the Association for Computers and the Humanities (ACH)’s ‘Next Steps’ document, “to explore relationships w/ DH-sympathetic orgs operating beyond the academy (Museum Computer Network, Nat’l Council on Public History, etc)”. At the request of ACH’s Bethany Nowviskie (@nowviskie) and Stéfan Sinclair (@sgsinclair), Eric D. M. Johnson and I had been tossing around some ideas for concrete next steps and working up to asking people working at the intersection of GLAM and DH for their input.

However, last night a conversation on twitter about DH and museums (prompted by Miriam Posner‘s tweet asking for input on a post ‘What are some challenges to doing DH in the library?‘) suddenly took off so I seized the moment by throwing the outline of the document Eric and I had been tinkering with onto Google docs. It was getting late in the UK so I tweeted the link and left it so anyone could edit it. I came back the next morning to find lots of useful and interesting comments and additions and a whole list of people who are interested in continuing the conversation.  Even better, people have continued to add to it today and it’s already a good resource.  If you weren’t online at that particular time it’s easy to miss it, so this post is partly to act as a more findable marker for the conversation about museums, libraries, archives and the digital humanities.

Explaining the digital humanities to GLAMs

This definition was added to the document overnight.  If you’re a GLAM person, does it resonate with you or does it need tweaking?

“The broadest definition would be 1) using digital technologies to answer humanities research questions, 2) studying born digital objects as a humanist would have studied physical objects, and or 3) using digital tools to transform what scholarship is by making it more accessible on the open web.”

How can you get involved?

Off the top of my head…

  • Add your name to the list of people interested in keeping up with the conversation
  • Read through the suggestions already posted; if you love an idea that’s already there, say so!
  • Read and share the links already added to the document
  • Suggest specific events where GLAM and DH people can mingle and share ideas/presentations
  • Suggest specific events where a small travel bursary might help get conversations started
  • Offer to present on GLAMs and DH at an event
  • Add examples of digital projects that bridge the various worlds
  • Add examples of issues that bridge the various worlds
  • Write case studies that address some of the issues shared by GLAMs and DH
  • Spread the word via specialist mailing lists or personal contacts
  • Share links to conference papers, journal articles, videos, podcasts, books, blog posts, etc, that summarise some of the best ideas in ways that will resonate with other fields
  • Consider attending or starting something like Decoding Digital Humanities to discuss issues in DH. (If you’re in or near Oxford and want to help me get one started, let me know!)
  • Something else I haven’t thought of…

I’m super-excited about this because everyone wins when we have better links between museums and digital humanities. Personally, I’ve spent a decade working in various museums (and their associated libraries and archives) and my PhD is in Digital Humanities (or more realistically, Digital History), and my inner geek itches to find an efficient solution when I see each field asking some of the same questions, or asking questions the other field has been working to answer for a while.  This conversation has already started to help me discover useful synergies between GLAMs and DH, so I hope it helps you too.

Update, November 2012: as a result of discussions around this document/topic, the Museums Computer Group (MCG) and the Association for Computers and the Humanities (ACH) worked together to create 5 bursaries from the ACH for tickets to the MCG’s UK Museums on the Web conference.