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Open GLAM presents global perspectives on open access to the cultural heritage in Galleries, Libraries, Archives and Museums (GLAMs). Submissions are welcome so please get in touch.

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IIIF is a set of open standards for delivering high-quality, attributed digital objects online at scale. It’s also an international community developing and implementing the IIIF APIs. IIIF is backed by a consortium of leading cultural institutions.

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Open approaches: aggregation and engagement at Europeana

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The Arts and Humanities Research Council (AHRC) today announced it has awarded £14.5 million as part of its Towards a National Collection programme to five major projects involved in the research and development of emerging technologies, including machine learning and citizen-led archiving, in order to connect the UK's cultural artefacts and historical archives in new and transformative ways.

One of these projects is Our Heritage, Our Stories: Linking and searching community-generated digital content to develop the people's national collection, which is a collaboration between the University of Glasgow, The National Archives and the University of Manchester.

In the past two decades communities have adopted digital technologies to gather and record their collections in a form of 'citizen history' that has created a truly democratic and vast reservoir of new knowledge about the past - known as community-generated digital content (CGDC). CGDC has proved extraordinarily resistant to traditional methods of linking and integration, for lack of infrastructure and the complexity of the content.

Our Heritage, Our Stories will bring together a powerful partnership, including researchers in digital humanities, archives, history and computer science with world-leading archive development to dissolve existing barriers and develop scalable linking and discoverability for CGDC.

The project will make CGDC more discoverable and accessible while respecting and embracing its complexity and diversity. This new accessibility will be showcased through a major new public-facing CGDC online Observatory at The National Archives where people can access, reuse and remix these newly integrated collections.
Valerie Johnson, Director of Research and Collections at The National Archives, said:
'We are genuinely excited to be a part of this programme. These important projects not only use emerging technologies to address the challenges of accessibility to the UK's culture and heritage collections but also dissolve barriers between the different collections of the UK.'

This project is part of Towards a National Collection, a five-year research programme, revealing the first insights into how thousands of disparate collections could be explored by public audiences and academic researchers in the future. One of the central aims is to diversify audiences by involving them in the research and creating new ways for them to access and interact with collections. In addition to innovative online access, the projects will generate artist commissions, community fellowships, computer simulations and travelling exhibitions.

For more information please visit www.nationalcollection.org.uk.

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Towards a National Collection - The National Archives

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The Arts and Humanities Research Council (AHRC) today announced it has awarded £14.5 million as part of its Towards a National Collection programme to five major projects involved in the research and development of emerging technologies, including machine learning and citizen-led archiving, in order to connect the UK's cultural artefacts and historical archives in new and transformative ways.

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Pedestal, web content management system for 3D data, The University of Melbourne

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Pedestal, web content management system for 3D data, The University of Melbourne

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Pedestal is a web content management system for 3D data for use in learning, teaching, research and outreach. The ability to upload content requires an account which can be applied for through the relevant division administrator.

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Before you head home to explore the objects and media that you've collected at ACMI, use your Lens to trigger the Constellation, a large-scale digital experience at the end of our centrepiece exhibition, The Story of the Moving Image. A galaxy of screen media bursts to life when the Lens and Constellation collide, revealing the fascinating streams of interconnected content that's been expertly curated by our staff.

Make discoveries at home

You don't need to visit ACMI to explore the Constellation - they're all available online.

So, if you've ever wondered how The Wizard of Oz connects to Cuphead, or the relationship between The Simpsons and Buffy The Vampire Slayer, start exploring how over 200 objects and media are connected to the cosmos of moving image content.

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Before you head home to explore the objects and media that you've collected at ACMI, use your Lens to trigger the Constellation, a large-scale digital experience at the end of our centrepiece exhibition, The Story of the Moving Image .

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Context

The Congruence Engine is a three-year research project starting in November 2021 that will use the latest digital techniques to connect industrial history collections held in different locations. It is one of five 'Discovery Projects' funded by the Arts and Humanities Research Council under the ' Towards a National Collection ' funding stream.

Aim

We will create the prototype of a digital toolbox for everyone fascinated by our industrial past to connect an unprecedented range of items from the nation's collection to tell the stories about our history that they want to tell; we will ask: What was it like then? How does our past bear on our present and future?

Until now, historians and curators have become used to a world where it has only been possible to work with a small selection of the sources - museum objects, archive documents, pictures, films, maps, or publications, for example - potentially relevant to the history they want to explore. We hope to overcome this major constraint on the histories that can be created and shared with the wider public in museums, publications and online.

The project will unite in collaboration a unique combination of skills and interests. Here, digital researchers will work alongside professional and community historians and curators.

Through 27 months of iterative exploration of the textiles, energy and communications industrial sectors, the project will tune collections-linking software to make it responsive to user needs. It will use computational and AI techniques - including machine learning and natural language processing - to create and refine datasets, provide routes between records and digital objects such as scans and photographs, and create the tools by which the historian and curator participants will be able to enjoy and employ the sources that are opened to them.

The new narratives they create will be expressed in the project's mobile digital exhibition space, on its website and in a slew of popular and academic outputs.

Project partners

National Museum Wales, National Museums Northern Ireland, Birmingham Museums Trust, The National Archives, National Trust, the V&A, BBC History, BT Heritage & Archives, Grace's Guide to Industrial History, Isis Bibliography of the History of Science, Society for the History of Technology, Saltaire World Heritage Education Association, Whipple Museum of the History of Science (Tools of Knowledge Project), Wikimedia UK and Manchester Digital Laboratory (MadLab).

Co-Investigators

Co-Investigators include researchers at:

Science Museum Group, The British Film Institute, Historic England, National Museums Scotland, Tyne and Wear Museums and Bradford Museums, and the Universities of Leeds, London and Liverpool, and UCL.

The Congruence Engine is funded by the Arts and Humanities Research Council's Towards a National Collection: Opening UK Heritage to the World fund.

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The Congruence Engine: Digital Tools for New Collections-Based Industrial Histories

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The Congruence Engine is a three-year research project starting in November 2021 that will use the latest digital techniques to connect industrial history collections held in different locations. It is one of five 'Discovery Projects' funded by the Arts and Humanities Research Council under the ' Towards a National Collection ' funding stream.

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Experiments in emerging technologies and visitor experience at the Science Museum Group (Science Museum, London; National Science and Media Museum, Bradford; National Railway Museum, York; Science and Industry Museum, Manchester; and Locomotion, Shildon).

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It has been just over a decade since the first public APIs appeared in the museum community. Usually released by institutions to encourage software developers and creative technologists to 'play' with the museum's collection data, APIs have much more become commonplace in recent times - especially as APIs are now part of most medium to large institution's IT back office wheelhouse.

If we think of a websiteas an easy way for people to read our museum data, then we can also think of an API as an easy way for computers to read that same museum data.

ACMI first released its collection data as a downloadable spreadsheet in 2016. We released the descriptive metadata of the former lending collection of films under the most open license available - Creative Commons Zero. It was integrated with a few 'union catalogues' and became the subject of some interesting data visualisation experiments in 2017. Then the ACMI renewal project took over and an expansion of this data aceess was put on hold while we got the new galleries into shape. Through the Renewal project, too, we rearchitected the technology stack at ACMI and made significant strides forward in improving the underlying collection data too.

Since re-opening the new ACMI in February 2021, the ACMI Labs creative technologists have been hard at work building the infrastructure for our first public collection API which compliments, and in many cases mirrors, our internal private APIs that drive our galleries, website and fall under the collective umbrella of XOS.

We wanted to make it easier for researchers and software developers to explore our ACMI Collection data - and we also wanted to better automate the publishing of the collection data in simple downloadable formats.

We think it might be useful for things like:

Building exciting new ways to visualise our collection data, revealing absences, strengths, and biases in what we hold, and how the collection has been described over the past 80 years

Matching our collection data with collection data from other institutions or data sources such as TMDB, IMDB, Wikidata or VIAF

Creating applications that extend and transform our collection data

For some of these tasks it will be easier to use the TSV or JSON data dumps, and for others, it may be easier to build an application that connects to our API.

The ACMI Collection API contains textual metadata for roughly 45,000 catalogued objects in the ACMI collection from films, videogames, artworks, home movies, and objects. This represents the majority of works in ACMI's collection but does not include carrier-level information - a specific work may appear on several carriers. For example, our 1960 instructional film, Mice Milking, has one work (title) record but six carriers - one analogue 16mm and 5 digital surrogates, each of which have different storage locations.

For complex licensing reasons and the in-Copyright status of almost all works in our collection we cannot provide access to images or videos, however we do provide identifiers which will allow you to find images of the same work in other online sources such as TMDB, and videos, where we do have permissions, in ACMI's YouTube.

Objects and works that are on loan to ACMI from other institutions and private collections are not included, nor are works from the wider worlds that are included in the Constellation interactive experience but do not also appear in our accessioned collection.

Some of the features we enjoyed building were:

Complete archive of JSON files included in the repository

TSV (tab separated values) spreadsheet of the entire dataset of works

Nightly updater to keep our public API data fresh

Docker development containers for researchers and software developers to run our API offline (including an ElasticSearch container)

Before releasing it to the world, we thought it would be best to put ourselves in the place of a person using it. Here's a few experiments we built which you can play with, and pull apart.

We chose to present these as Juypter Notebooks on Google Colab so you don't need to spin up any software on your own computers to try them, or to see how they work.

Machine Dreaming stepping through its predictions of what Mad Max looks like based on the textual metadata written by our cataloguers and curators (no images were supplied

Machine Dreamingis an experiment that uses the VQGAN+ CLIP machine learning algorithms to process the textual description of a work and to 'dream' images based on that metadata. When you have a collection but cannot show any images, perhaps it might be interesting for a computer to generate some 'alternative' images instead!

This sort of 'machine dreaming' can also be quite revealing about what the image generation algorithm has been 'trained' on - showing specific biases that make some things appear closer to our own understandings of the meaning of a paragraph of text than others.

Here's what the machine dreamt from our metadata against the ImageNet training dataset:

['Mad Max', 'George Miller's Mad Max revolutionised movies when', 'it tore through cinemas in 1979. Bursting', 'with stunning practical effects, explosive set pieces', 'and iconic costumes, the original Mad Max', 'trilogy (1979-85) cemented its place in pop', 'culture before roaring back to life 30', 'years later.']

Mad Max, as dreamt by a computer from the ACMI Public API Work metadata for Mad Max.

And here a rather Cronenberg-inspired body horror imagining of the aforementioned Mice Milking metadata:

[Mice Milking', 'Please be advised this film contains scenes', 'of animal restraint that some viewers may', 'find disturbing.This film, made by the Victorian', 'Department of Agriculture, documents the process by', 'which mice are milked in a laboratory', 'at the Safe Research Farm in Werribee,', 'for use in cancer research. The narrator', 'explains that in mice, leukemia and mammary', 'cancer are similar to cancer in humans', 'and the virus is present in their', 'milk. The mice milking machine in use', 'in the film was developed by research', 'officer Graeme Mein for demonstration in an', 'open day at Werribee, based on those', 'used by the National Cancer Institute, USA.', 'The film shows laboratory technicians attaching a', 'mouse to the machine and milking them.']

Mice Milking as dreamt by a computer from the ACMI Public API Work metadata for Mice Milking.

You can try it for yourself in our Jupyter Notebook on Google Colab. You will need to enter a record ID and can choose different training datasets from ImageNet to WikiArt. A single record may take up to 20 minutes to tun through the full generation process.

The output from Google Colab showing it matching Wikipedia biographies to our ACMI Public API's creators

Wikipedia Biographiesis a very simple search example that prompts for a Work ID and then looks for matches for all its related credits in Wikidata/Wikipedia biographies. With the output of this you build different indexes of named entities within ACMI's collection data, complete with biographies and other external authority IDs which can be used to disambiguate people with common names.

Try it yourself in our Juypter Notebook on Google Colab.

There's a page of documentation over on our website at www.acmi.net.au/apiwith instructions for exploring our API and collection data.

During the renewal project the ACMI Labs team built a bunch of private APIs that are run on XOS (ACMI's eXperience Operating System). The computers in our centrepiece exhibition use these private APIs to talk to each other:

Media Players use our Playlists and Videos APIs to download and play moving image content

Digital Labels use our Playlists, Collection, and Labels APIs to display interactive museum labels

Lens Readers use our Taps API to allow visitors to collect objects in the exhibition they like

Constellation Tables use our Constellations APIto show visitors everything they collected during their visit, and connections to other objects in our collection they might also like

Our ultimate goal is to make all of these private APIs public, and to do this we needed to decouple the public API from the museum completely, to allow it to be as accessible and fast as possible, and also to keep our museum network of ~400 computers safe from outside attacks.

We wanted to use Python, the same programming language that we've used for XOS, the ACMI Website, and all of our SOMI gallery devices, so we chose Flask to build our public API.

We've open sourced our API server here: github.com/ACMILabs/acmi-api

If you get stuck, or find a bug, feel free to get in touch with us either via Twitter at @ACMILabs, or via the contact information on our website: https://www.acmi.net.au/contact/

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Introducing the ACMI Public Collections API

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It has been just over a decade since the first public APIs appeared in the museum community. Usually released by institutions to encourage software developers and creative technologists to 'play' with the museum's collection data, APIs have much more become commonplace in recent times - especially as APIs are now part of most medium to large institution's IT back office wheelhouse.

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A collection of tools and examples to help you work with data from galleries, libraries, archives, and museums

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Science Museum Group Collection: Never Been Seen

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Science Museum Group Collection: Never Been Seen

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Explore objects from the Science Museum Group Collection never seen online before thanks to a new digitisation tool.

We start 2021 with three big milestones for the Science Museum Group Collection.

100,000 incredible objects now have a photograph online, the online collection regularly receives 100,000 views each month and we've just recorded 3,000,000 visitors since launching the website in late 2016.

Each time you visit our online collection you can see more than ever before.

Almost a quarter of the remarkable objects we care for (24.9% or 105,715 objects to be exact) have a photograph online, with hundreds of new photographs added each month as we digitise our vast collection.

You can explore photographs of artworks, tools and video games, or items from astronomy, firefighting and printing to give a few examples from the collection (which can be seen below).

Zoom in on the amazing detail in an Apollo 11 lunar chart, or study aerial images from across the world, a Chinese star map or this colourful geological diagram.

In the past we've released digital tools to help you explore the collection, including our Random Object Generator, Museum in a Tab (a Google Chrome extension) and What the machine saw (a machine learning experiment). You can even add our objects to the popular game Animal Crossing.

However, it can be difficult to spot recently photographed objects in the collection. So today we have published a new tool to help you explore these new items.

Never Been Seen

Never Been Seen shows objects from the Science Museum Group Collection that have never been seen online before.

Each time you refresh this webpage an object with zero views is shown, making you the very first person to see it. To try it just click on the link above, or the image below.

We're adding new photographs online all the time, so spend a few minutes with the collection and be the first in the world to discover an object that has never been seen online before.

If you would like to know more, you can examine the code behind the tool on our Github site.

Never been seen has been released as part of our ambitious project to share more of the Science Museum Group Collection with audiences across the world.

We are working hard to study, photograph and digitise hundreds of thousands of objects as they are moved to a new home at the National Collections Centre in Wiltshire, which will open for public tours, school and research visits once the object move is completed.

Regular updates on the project are provided through this blog series.

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Explore objects from the Science Museum Group Collection never seen online before thanks to a new digitisation tool. We start 2021 with three big milestones for the Science Museum Group Collection. 100,000 incredible objects now have a photograph online, the online collection regularly receives 100,000 views each month and we've just recorded 3,000,000 visitors since launching the website in late 2016.

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There are 84 countries represented in our online collection spanning 78,373 objects, which means that about 35.98% of all our stuff has a country to call home.

A note about the countries listed here: These are only those countries for which we were able to successfully match an object's stated location against the Where on Earth (WOE) gazetteer. Eventually every object will have a unique gazetteer ID (whether it's WOE or the Getty's thesaurus of named places or some other source) but that's not the case at the moment, partly because in the push to release the beta version of the website we've opted for things that could be solved programatically with a high degree of confidence and left things that need extra checking to identify, whether by humans or machines, for later.

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There are 84 countries represented in our online collection spanning 78,373 objects, which means that about 35.98% of all our stuff has a country to call home. A note about the countries listed here: These are only those countries for which we were able to successfully match an object's stated location against the Where on Earth (WOE) gazetteer.

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 Cleveland Museum of Art: VIRTUAL CMA DASHBOARDS

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 Cleveland Museum of Art: VIRTUAL CMA DASHBOARDS

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Since launching our Open Access Initiative in January of 2019, the Cleveland Museum of Art has been asking, "How is Open Access making an impact?" Since launch, we have been collecting data across multiple platforms, hoping to gather insights. Thanks to the work CMA has done on our back-end systems for the past decade, we were able to launch our Open Access API and dynamically share our collection on multiple repositories across the web, such as Internet Archive, Creative Commons, Wikipedia, and ArtStor.

As the museum temporarily closed its doors in March of 2020 due to the COVID19 pandemic, we immediately saw a rise in views on our Collection Online - this lead us to wonder if there were similar patterns in Open Access downloads and views across repositories. With the help of local data science firm Pandata, CMA launched these live dashboards, which update daily. Click through the tabs on the top of the page to view different data sets. Sort by date or filter by department. What are the most viewed and downloaded artworks?

It's exciting to see how different the museum's top 50 are in comparison to our top artworks on Wikipedia, and the explosive, exponential effect that our partner repositories have had on the international reach of our collection. Comparing how the public interacts with our collection on CMA's collection online, our API, and partner repositories such as Wikipedia, can help inform not only our future decisions, but hopefully inspire others in the museum community to extend the reach of their collections. Being transparent with our data is important to the CMA as an extension of our Open Access initiative and the museum's mission.

As of now, we are displaying data for our Collection Online, our Open Access API, and Wikipedia. Check back soon, as we plan to add data on more of our partner repositories, such as Internet Archive, Creative Commons and ArtStor.

Find something interesting in our data? Let us know at openaccess@clevelandart.org.

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Since launching our Open Access Initiative in January of 2019, the Cleveland Museum of Art has been asking, “How is Open Access making an impact?” Since launch, we have been collecting data across multiple platforms, hoping to gather insights. Thanks to the work CMA has done on our back-end systems…