The British Library Universal Viewer team were delighted to attend the IIIF conference and showcase 2024 at UCLA in Los Angeles, California. This was our the first official event since the team formed earlier in the year, and we felt incredibly fortunate to be travelling across numerous time zones to join over 70 members of the IIIF community for four days of innovation, learning and inspiration. 

The Universal Viewer team outside the De Neve Plaza at UCLA

The first two days of the conference were held at the De Neve Plaza and took the form of lightning talks from delegates from a variety of different industries, and on many different topics. This format meant there was something to interest everyone, regardless of experience, and was great for keeping concentration levels high despite the jet lag! 

Birds of a feather sessions were held on the third day of the conference, with a last-minute entry from the Universal Viewer team – although lack of space meant that this was an impromptu meeting in the Kerckhoff Coffee House. However, this meant we were able to plan future work, specifically on annotations, in the sunshine on the terrace. 

Attendees of the UV Birds of a Feather session at the Kerckhoff Coffee House

Here were the exciting takeaways! 

Lanie Okorodudu: I was interested on how IIIF resources and IIIF-related tools could be used as a part of curriculums in online learning platforms to create meaningful knowledgeable experiences for students. I was also intrigued by “Tropiiify”, which is a plug-in for exporting IIIF collections and designed for non-technical users. 

Erin Burnand: I loved hearing about how IIIF can provide innovative solutions for incredible (but complex) collections such as the Judy Chicago Research Portal (Pennsylvania State University Library) and the work on Eastern Silk Road collections for the International Dunhuang Programme (presented by the BL’s Anastasia Pineschi) 

James Misson: The conference was an amazing opportunity to connect with fellow IIIF users, from IIIF newcomers, to those who helped define the original specifications. I enjoyed hearing work on the carbon footprint of OCR, and the transformation of historical textiles into sound to make an exhibition more accessible to visually impaired people. It was inspiring to see the range of uses IIIF has, and I was especially excited by Allmaps (allmaps.org), a toolbox for working with IIIF maps. The conference was a testament to how open the IIIF community is, and everyone generously shared their knowledge with our new team – conversations that continued in the bars of Westwood and In-n-Out Burger. 

Saira Akhter: I found the discussions on the use of AI within IIIF interesting, such as for facial recognition within historic photographs and future integration with OCR/HRT tools and outputs. The showcase at the Getty was great for learning more about IIIF itself, and it was cool to see how the idea for IIIF was first written on a napkin at a restaurant. I also enjoyed seeing more novel uses of IIIF, such as for importing paintings into Animal Crossing. 

Recordings of the conference are now available on YouTube.   

This is a repeated and updated blog post by Dr Adi Keinan-Schoonbaert, Digital Curator for Asian and African Collections. She shares some background information on how a new post advertised for a Digital Curator for OCR/HTR will help the Library streamline post-digitisation work to make its collections even more accessible to users. Our previous run of this recruitment was curtailed due to the cyber-attack on the Library - but we are now ready to restart the process!

 

We’ve been digitising our collections for about three decades, opening up access to incredibly diverse and rich collections, for our users to study and enjoy. However, it is important that we further support discovery and digital research by unlocking the huge potential in automatically transcribing our collections.

We’ve done some work over the years towards making our collection items available in machine-readable format, in order to enable full-text search and analysis. Optical Character Recognition (OCR) technology has been around for a while, and there are several large-scale projects that produced OCRed text alongside digitised images – such as the Microsoft Books project. Until recently, Western languages print collections have been the main focus, especially newspaper collections. A flagship collaboration with the Alan Turing Institute, the Living with Machines project, applied OCR technology to UK newspapers, designing and implementing new methods in data science and artificial intelligence, and analysing these materials at scale.

OCR of Bengali books using Transkribus, Two Centuries of Indian Print Project

Machine Learning technologies have been dealing increasingly well with both modern and historical collections, whether printed, typewritten or handwritten. Taking a broader perspective on Library collections, we have been exploring opportunities with non-Western collections too. Library staff have been engaging closely with the exploration of OCR and Handwritten Text Recognition (HTR) systems for English, Bangla, Arabic, Urdu and Chinese. Digital Curators Tom Derrick, Nora McGregor and Adi Keinan-Schoonbaert have teamed up with PRImA Research Lab and the Alan Turing Institute to run four competitions in 2017-2019, inviting providers of text recognition methods to try them out on our historical material.

We have been working with Transkribus as well – for example, Alex Hailey, Curator for Modern Archives and Manuscripts, used the software to automatically transcribe 19^th century botanical records from the India Office Records. A digital humanities work strand led by former colleague Tom Derrick saw the OCR of most of our digitised collection of Bengali printed texts, digitised as part of the Two Centuries of Indian Print project. More recently Transkribus has been used to extract text from catalogue cards in a project called Convert-a-Card, as well as from Incunabula print catalogues.

An example of a catalogue card in Transkribus, showing segmentation and transcription

We've also collaborated with Colin Brisson from the READ_Chinese project on Chinese HTR, working with eScriptorium to enhance binarisation, segmentation and transcription models using manuscripts that were digitised as part of the International Dunhuang Programme. You can read more about this work in this brilliant blog post by Peter Smith, who's done a PhD placement with us last year.

The British Library is now looking for someone to join us to further improve the access and usability of our digital collections, by integrating a standardised OCR and HTR production process into our existing workflows, in line with industry best practice.

For more information and to apply please visit the ad for Digital Curator for OCR/HTR on the British Library recruitment site. Applications close on Sunday 21 July 2024. Please pay close attention to questions asked in the application process. Any questions? Drop us a line at [email protected].

Good luck!

This blog post is by Dr Adi Keinan-Schoonbaert, Digital Curator for Asian and African Collections, British Library. She's on Mastodon as @[email protected]. 

 

Last April I was part of a British Library delegation to China, which was a wholesome and fulfilling experience. It aimed to refresh collaborations and partnerships with the National Library of China and the Dunhuang Academy, explore new connections and strengthen existing ones with many other institutions and individuals. I will explore this trip from a digital scholarship lens, but you can read all about the trip and its larger aims and accomplishments in a post on the IDP blog by International Dunhuang Programme Project Manager, Anastasia Pineschi. 

The Mogao Caves in Dunhuang

My primary objective was to attend and present at the IDP conference (19-20 April 2024), co-organised by the British Library and the Dunhuang Academy and synchronised with IDP’s 30th anniversary and the launch of a new, fresh and accomplished IDP website. Sharing our work and learning from others during this conference and the IDP workshop that took place the following day was one of my objectives. But I was also looking to reconnect with peers and getting to know new colleagues working in the fields of DH and the interchange of AI, cultural heritage and historical digital collections; explore opportunities for collaboration in the field of OCR/HTR (Optical Character Recognition, Handwritten Text Recognition); and get ideas for DH opportunities for IDP. 

British Library and Dunhuang Academy colleagues in front of Mogao Cave 96 (Nine Story Temple)

Colleagues from the Dunhuang Academy showed us such outstanding hospitality, with our Dunhuang trip including many behind-the-scenes visits and unique experiences. These included, naturally, the extraordinary Mogao Grottoes, but also another cave site called the Western Thousand Buddha Caves, and stunning natural spots such as the Singing Sand Dune (Mingsha Mountain) and the Crescent Moon Spring. We also visited places such as the Digital Exhibition and Visitor Center, the Multi-field lab at the Dunhuang Studies Information Center, the Grottoes Monitoring Center and Conservation Lab, and the Dunhuang City Museum. All have left long-lasting impressions. 

One of the dashboards managing the Mogao Grottoes at the Grottoes Monitoring Center

But let’s get back to the main purpose of this post, which is to report on some of the outstanding work happening out there at the intersection of Chinese historical collections and DH.

 

Conference (DH) Highlights  

I’ll start with one of the earliest platforms to enable and encourage DH research in the context of Chinese works, the Chinese Texts Project. Dr Donald Sturgeon (Durham University) presented about this well-known digital library of pre-20th century Chinese texts, which started in 2005 and is still impressively active at present, being one of the largest and most widely used digital libraries of premodern Chinese texts. Crowdsourcing and AI are now used to enhance the texts available via this platform. Machine Learning OCR is used to automate transcriptions, automated punctuation is added through deep learning, and OCR corrections are done via a crowdsourcing interface. This sees quite a high volume of engagement, typically ca. 1,000 edits per day! Sturgeon also talked about the automated annotation of named historical entities in transcribed texts, as well as using deep learning to assert periods and dates, being able to transition between Chinese and Western calendars. These annotations can then turn into structured data – enabling linking up to other data. 

Dr Donald Sturgeon presents about extracting structured data from annotations

While on the topic of state-of-the-art platforms, Prof Kiyonori Nagasaki (International Institute for Digital Humanities, Tokyo) talked about the SAT Daizokyo Text Database, a digital editing system for Buddhist canons and manuscripts using AI-OCR developed and recently released by the National Diet Library of Japan. The IIIF-compliant database of Buddhist icons annotated over 20,000 items, enabling search by various attributes. Nagasaki gave us a website demo, displaying an illustration with 400 annotations. One can search annotated parts of this image and compare images in the search results. Like the Chinese Texts Project, the SAT platform also incorporates crowdsourcing ‘editing’ with clever Machine Learning techniques. It was good to hear that there is an intention for SAT to gradually include Dunhuang manuscripts in the future. 

Prof Kiyonori Nagasaki demonstrated how the interface interaction is facilitated by IIIF: clicking on the text bring up the right area in the IIIF-image

Another well-established, IIIF-based system, presented by Dr Hongxing Zhang (V&A Museum), is the Chinese Iconography Thesaurus (CIT). CIT has been an ongoing project since 2016, developed at the V&A and aiming to work towards subject indexing standard for Chinese Art. A system of controlled vocabulary is crucial to improve access to collections and linking up multiple collections. CIT focuses on Chinese iconography – motifs, themes, and subject matters of cultural objects, with almost 15,000 concepts and entities. And, it’s IIIF-supported – images and annotations can be viewed in IIIF Mirador lightbox. 

Not just Chinese

While much of the work around Dunhuang or Silk Road manuscripts has to do with Chinese language, several scholars emphasised the importance of addressing other languages as well. Dunhuang manuscripts were written in languages such as Sogdian, Middle Persian, Parthian, Bactrian, Tocharian, Khotanese, Sanskrit, Tibetan, Old Uighur, and Tangut. Prof Xinjiang Rong (Peking University) emphasised the importance of providing transcriptions, transliterations and translations alongside digitised images. These languages require special language expertise; therefore, cooperation between institutions and scholars is crucial. Prof Tieshan Zhang (Minzu University of China) also urges researchers to address and publish non-Chinese Dunhuang manuscripts. He especially highlighted the importance of making better use of text recognition technologies for languages other than Chinese. Last year, the Computer Science department of Minzu University of China applied for a research project to do just that. They started with non-Chinese languages and aim to increase recognition accuracy to over 90%. 

The talk by Prof Hannes Fellner (University of Vienna) came as a perfect example of how one could address the study of material in other languages, using computational methods. He introduced a project aiming to trace the development of Tarim Brahmi – one of the major writing systems of the Eastern Silk Road during the 1st millennium CE, which includes Khotanese, Sanskrit, Tocharian, and Saka. The project compiles a database of characters in Tarim Brahimi languages (currently primarily Tocharian), with palaeographic and linguistic annotations, presented as a web application. With the aim to create a research tool for texts in this writing system, such platform could facilitate the study of palaeographic variation, which in turn could help explore scribal identification, language development stages, and correlations between palaeographic and linguistic variations. Fellner works with Transkribus and IIIF to retrieve the coordinates of characters and words, returning the relevant ‘cut-outs’ of the photos to the web application. These can then be visualised, displaying character or word variations alongside their transliteration. 

Prof Hannes Fellner shows how working with Transkribus and IIIF makes it possible to retrieve ‘cut-outs’ from photographs corresponding to the query string

Coming back to Chinese OCR/HTR, there’s quite a lot of activity in this area. I presented about work at the British Library aiming to advance Chinese HTR methods, in the wider context of the Library’s OCR/HTR work. We’ve focused on using the eScriptorium platform by collaborating with Colin Brisson (École Pratique des Hautes Études) and the French consortium Numerica Sinologica (now working on the READ_Chinese project). I talked about the work of our PhD Placement student, Peter Smith (University of Oxford), contributing to processes such as binarisation, segmentation and text recognition. I have recently presented about this work at Ryukoku University in Kyoto, and you can read more about it in Peter’s excellent blog post. 

Dr Adi Keinan-Schoonbaert talking about OCR/HTR activities at the British Library

 

Dunhuang online platforms

It is crucial to embed such technologies and software into user-friendly platforms, where different functionalities are available for different types of needs and audiences. Dr Peter Zhou (University of California, Berkeley) talked about the importance of building a sustainable platform that can support the complete digital lifecycle, including data curation and management, long-term preservation, and dissemination. Zhou’s objectives for the Digital Dunhuang platform are to connect resources that are otherwise isolated, featuring uniform standards for data exchanges. Such platform must enable different kinds of data formats, including raw images, historical photos, videos, cave QTVRs, digitised texts and artifacts, reproductions, microfilm, interactive visuals, conservation data, spatial info, 3D modelling data, and immersive media. This Digital Dunhuang platform should be flexible, able to scale up and deal with mass content in different formats, have Machine Learning capabilities, and aggregating knowledge content through linking.  

We can see many of these elements in a platform developed by the Dunhuang Academy. Xiaogang Zhang and Tianxiu Yu of the Dunhuang Academy introduced the Digital Library Cave platform (Digital Dunhuang), built in collaboration with Tencent, and its plans. The platform presents both a database of Dunhuang materials and murals, as well as a playable game focused on the narrative of the Library Cave. This platform displays an engaging, immersive mixture of 3D environments and artifacts, in addition to 2D items. The aim for the Digital Dunhuang platform is to present digital resources relating to the Mogao Grottoes in one integrated and comprehensive resource for Dunhuang studies. (Side note: access to the database requires a login and input of personal data). 

Tianxiu Yu showing a Knowledge Graph connecting different types of data resources

The richness and variety of data available now and in future on this platform is remarkable. The entire cliff of the Mogao Grottoes and some of the large-scale cultural relics are available in 3D, and this is complemented by other data used in conservation and research. And there’s an impressive array of AI technologies applied to both images and texts. For images, murals dataset annotations and automatic object detection would allow for search and retrieval; AI used for image enhancements for old photos; line drawing are extracted from art scenes; and image stitching automation. For texts, functionalities will include, at a later stage, character text recognition, providing full text retrieval at 90% precision rate; Traditional to Simplified Chinese conversion; automatic punctuation; entity extraction; and the creation of knowledge graphs. When completed, this platform will be open and share all resources available online. 

With a solid focus on text retrieval and analysis, Dr Xiaoxing Zhao (Dunhuang Academy) presented about the Dunhuang Documents Database, collating digitised manuscripts and prints dating from the 4th to the 11th centuries discovered in the Library Cave at Mogao, Dunhuang. Providing full-text retrieval for Chinese, Tibetan, and Uighur (and a plan to add Tangut), it includes search functionality using keywords, and features transliteration in Traditional Chinese, which can be conveniently viewed alongside the image. It’s great to see how far AI text recognition has come! 

Dr Xiaoxing Zhao demonstrating the Dunhuang Documents Database’s transliteration in Traditional Chinese, which can be seen side by side to the image

However, technological advances are not just restricted to AI and Machine Learning. Prof Simon Mahony (Emeritus Professor, UCL) gave a fascinating, image-rich talk about non-invasive and non-destructive computational imaging of ancient texts. Mahony introduced different techniques to address research questions arising from textual manuscripts. These methods allow, for example, reading illegible texts and seeing artworks, determining the composition of pigments, or detecting characteristics of ink. One of the projects that he was involved with was the Great Parchment Book project. Damaged in a fire, the book’s content became inaccessible for researchers – but a series of steps taken to digitally straighten, flatten and stretch the book, turned it back to a readable state. This and other computational methods applied to images are indeed very inspirational! 

Prof Simon Mahony talking about how computational methods were used to enable the reading of the text in the Great Parchment Book project

 

Back to Beijing 

Coming back to Beijing, we had several visits such as the National Library of China and the Palace Museum’s Conservation Department. But I’ll focus here on two visits which are directly related to DH and computational methods – the first at the Chinese Academy of Sciences (CAS), and the second at the National Key Laboratory of General Artificial Intelligence, Peking University. 

We were kindly hosted by Prof Cheng-Lin Liu from the State Key Laboratory of Multimodal AI Systems (MAIS), Institute of Automation, CAS, and joined by Drs Fei Yin, Heng Zhang, and Xiao-Hui Li. Prof Liu gave an excellent keynote talk at the Machine Learning workshop at the ICDAR2023 conference, which I attended in August 2023. It was about “Plane Geometry, Diagram Parsing and Problem Solving,” which well exemplifies MAIS’ areas of work. It is a national platform specialising in document analysis, computer vision, robotics, Machine Learning, Natural Language Processing (NLP), and medical AI research – the first to start Pattern Recognition research in China, and one of its main AI research centres. We enjoyed an excellent exchange – and a fruitful discussion.  

MAIS and British Library colleagues at the CAS offices in the Haidian District, Beijing

 

From there, we travelled to Peking University for another stimulating knowledge exchange meeting with Prof Jun Wang, Director of the Research Center for Digital Humanities (PKUDH) and Vice Dean, Artificial Intelligence Institute, joined by Dr Qi Su, Dr Pengyi Zhang, Dr Hao Yang, Honglei San, Kairan Liu, and Siyu Duan. We watched videos of two Shidian platforms – open access web platforms for reading, editing and analysing ancient Chinese books, developed through a partnership between PKUDH and the Douyin Group. One platform is the Open Access Ancient Book Reading Platform, and the second is the AI-powered Ancient Book Collation Platform. The AI-empowered editing and compiling system includes an impressive array of functionalities. 

Screenshot from the YouTube video, showing features of the Shidian reading platform

Our session also included presentations and discussions around topics such as AI character reconstruction, cultural heritage curation and crowdsourcing, automatic text annotation and linked data. For example, PhD student Siyu Duan (supervised by Prof Su Qi) presented about dealing with ancient ideograph restoration, including a little experiment on Dunhuang data that showed suggested restoration of damaged or illegible characters. The whole session was an absolute delight!  

I am so grateful for everyone generosity and hospitality – I have learned so much, so thank you. Until next time! 

Dr Adi Keinan-Schoonbaert enjoying the dunes and the Crescent Moon Spring, Dunhuang

 

In this guest post, developer Sak Supple describes his work turning digitised images of playbills into fully searchable documents... Digital Curator Mia Ridge says, 'we're absolutely delighted by Sak's work, and hope that his post helps others working with digitised collections'.

Sample playbills from the British Library's collection

This blog post explores the creation of blplaybills.org, a website that showcases data made publicly available by the British Library.

The blplaybills.org website provides a way to search for, view and download archival playbills from Great Britain and Ireland, 1600-1902, as curated by the British Library (BL).

The website is independently produced using assets made available by the British Library under a Creative Commons licence as part of an open data initiative.

The playbill data

Playbills were promotional flyers advertising entertainment events at theatres, fairs and pleasure gardens.

The BL playbills data originated as document scans (digitised from microfilm, the most viable approach for fragile artefacts) in PDF format, each file containing hundreds of individual playbills, grouped by volume (usually organised by theatre, region and/or period of history).

In total there are more than 80,000 scanned playbills available.

Beside the PDFs, there is also metadata describing where in the Library these playbills could be found (volumes, shelfmarks etc). Including this information meant researchers could search for information online, and also have the volume reference at hand when visiting the Library.

This data is useful to anyone researching theatre, music, history and literature. Making it easy to find, view and download playbills using simple text searches over the internet is a good way to bring the playbills to a wider audience.

This is how blplaybills.org came into existence: the goal was to turn playbill data from the British Library into a searchable online database and image store.

The workflows

It is notoriously difficult to search PDF documents containing scans.

The text in these playbills is embedded in an image. This makes it especially difficult for computers to search the content of a scan, since a computer will interpret the text as a number of lines and curves within the image, without recognizing it as text.

Because internet technologies are well suited to searching for text, the first challenge is to turn the scanned playbill text into searchable text that a computer can more easily understand.

The chosen approach was to use Optical Character Recognition (OCR) software to capture text contained in the playbills.

OCR is a pattern matching technique, enhanced with machine learning, that finds text in an image by first using text detection algorithms to isolate character images, called glyphs, and comparing these with similarly stored glyphs. These glyphs are then further broken down into features (lines, loops etc), which are then used to find the best match amongst pre-trained glyphs.

The recognised text can then be processed using techniques like contextual analysis and grammar checking to improve accuracy.

The result can then be stored in a computer file to form text that a computer can recognise in the form of characters, words, phrases and sentences.

The resulting text is associated with individual playbills and related metadata, and the text and metadata stored in an online database to make it searchable.

In parallel to the above processes, high and low resolution JPEG versions of individual playbills were generated and uploaded to cloud storage for online access.

The general flow is shown below.

Figure 1: Flow of data from original data to structured online resources

The details of each of these workflows is discussed in more detail below.

Text generation workflow

Since the goal is to make it possible to search for individual playbills, the first step was to break up PDFs containing multiple playbills into individual documents containing one playbill each.

This was done using open source software called poppler-utils that provides command line utilities for manipulating PDF documents, including generating single page documents from one multipage document.

The next step is to extract text using OCR. In 2018 my research showed that an effective open source solution for this was Tesseract.

Experiments showed that Tesseract produced best results by converting the PDF document to a lossless raster format like TIFF (Tag Image File Format) before running the OCR program. In fact, it was found that changing the size of the document, increasing the resolution and contrast and then converting to TIFF produced good output from Tesseract OCR.

The conversion from PDF to TIFF for each playbill was achieved using open source software called ImageMagick.

This workflow is shown below.

Figure 2: Workflow to produce OCR text for each individual playbill

Doing this for 80,000+ individual playbills was achieved by automating the above workflow and processing multiple playbills in parallel. The individual playbills could be uniquely identified by the name of the original multipage PDF, together with the page number of the playbill.

Two other workflows were set up to work in parallel with this:

• Convert individual PDF playbills into high and low resolution JPEGs for online viewing
• Add metadata to the OCR text (volume, shelfmark, date, theatre etc) to produce a JSON file, and upload and index this information in a searchable online database

JPEG generation

As individual PDF playbills were generated from multipage PDFs, a copy of each single page PDF was sent to the JPEG generation workflow where its arrival triggered the workflow.

ImageMagick was used to create thumbnail and high resolution JPEG versions of the playbill suitable for online viewing.

The resulting JPEG files, identified by the original PDF filename and page number of the playbill, were then uploaded to cloud storage.

JSON generation

A popular choice to store searchable text in JSON format is a database called Elasticsearch. This provides fast indexing and search capabilities, and is available for non-commercial use.

This JSON should include the searchable playbill text and relevant metadata.

Each output from the text generation workflow triggered the JSON generation, allowing metadata for the individual playbill to be merged with OCR text into a single JSON file.

The resulting JSON was uploaded and indexed in an online Elasticsearch database. This became the searchable datastore for the web application that researchers use when visiting blplaybills.org.

The search interface

At this point the data is stored in a searchable online database, and images of individual playbills have been made available in online cloud storage.

The next step is to allow researchers to search for, view and download playbills.

The main requirements of the interface are:

• Simple text search to return playbills containing matching text
• These results to be quickly filtered using faceted search based on date, theatre, location, organisation and volume
• Quick copy of playbill text
• View and download a high resolution version of the playbill
• Responsive design

The interface is shown in Figure 3 below.

Figure 3: Online search interface

The web interface is hosted in AWS/EC2 (Amazon Web Services cloud compute service) and uses standard web frameworks used for the creation of single page applications.

Software development

Wherever open source software was available it was used: Tesseract, ImageMagick and poppler-utils.

Some software development was necessary to create backend workflows, and to automate and integrate them with each other.

This was achieved using a combination of scripting (NodeJS, Bourne shell and Python) and C programs.

The front-end was developed with Javascript, NodeJS, Angular and HTML5/CSS3.

Recent work and next steps

I recently made some modifications to the above approach to improve the quality of OCR generated text for each playbill.

Specifically, Tesseract has been replaced by a utility called textra (Swift/MacOS) that uses the Apple Vision framework for character recognition. This significantly improved the quality of the text generated by the OCR process, resulting in improved search accuracy. This technology was not available in 2018 when blplaybills.org was first created.

Another method to improve the accuracy of search might be to enhance OCR text with text transcribed as part of a crowdsourcing initiative from the British Library: In the Spotlight. This involved members of the public transcribing titles, names and locations in playbills. By adding this information to the indexed data already generated, search accuracy could be further improved.

An interesting piece of research would be to consider if LLMs (Large Language Models) could be fine tuned to enhance the results of traditional OCR techniques.

The goal would be to find a generalised approach that uses modern natural language processing techniques to improve the automatic transcription of less machine-readable archival material such as, but not limited to, these playbills. Ideally these techniques could also be applied to multi-lingual material.

This will be the focus of future work to improve the data behind blplaybills.org.

Digital Curator Mia Ridge with an update... Last year we posted about the British Library building a dedicated product team to work on the Universal Viewer (an item viewer that can display images, audio, video and even 3D versions of digitised and born-digital library collections), based on the IIIF standard for interoperable images and other media. We're now delighted to introduce the team. I asked them to write a brief note of introduction, mentioning what they've been working on or like about the UV and IIIF. They'll be at the IIIF conference in LA next week, so do say hi if you spot them. 

We'd also love to hear from people interested in improving the Universal Viewer's UX in line with current expectations - more below!

Meet the Universal Viewer Product Team

Erin Burnand, Product Owner: I am responsible for developing the product's vision, goal and strategy, and work with stakeholders to ensure we get the best possible product. I have over 20 years experience working in GLAMs (galleries, libraries, archives and museums), most recently working in the British Library's Collection Metadata Authority Control team.

I love the way IIIF presents so many opportunities to be creative with our collections, and how imaginative the community are - I am looking forward to exploring these ideas to engage with our audiences as British Library services begin to be restored.

Lanie Okorodudu, Senior Test Engineer: I joined the British Library in March this year and have been working on testing the functionality of IIIF and UV implementations, new features, bug fixes and updates to ensure they meet our high quality standards. I appreciate the robust and flexible framework packed with features that IIIF offers as these are necessary for efficient testing and validation of digital content delivery systems. 

James Misson: I am a Research Software Engineer with an academic background in the digital humanities and book history, currently working on improving developer documentation for the Universal Viewer to facilitate contributions from the community. I enjoy how generous and open the IIIF community is with sharing knowledge and expertise.

Saira Akhter, Research Software Engineer: I joined the Library as part of the Universal Viewer product team back in November. I’ve been working on enhancing the settings dialogue by adding new options and fixing bugs to improve compatibility with various file formats. I like that the UV code is configurable, which allows for flexibility and easy adaptation across different institutions. 

Erin, Lanie, James and Saira

Say Hi at the IIIF conference!

The team will be hosting a Universal Viewer 'live' community call at the 2024 IIIF conference in Los Angeles. Join them at the Kerckhoff Coffee House at 10 - 11.30am on Thursday June 6th where they'll update on recent team activities including work on the user experience of transcribed text (a collaboration with the Swedish National Archive) and improving documentation to make it easier for newcomers to UV to participate in the community. 

What are they working on?

In addition to their comments above, the team have spent some time working through practical questions with the UV Open Collective - the process for pull requests, testing, documentation, and developing and sharing our roadmap. 

We've also been talking to folks at Riksarkivet (the Swedish National Archives), as they're working on implementing a search function within transcriptions displayed on the viewer. If you're involved in the IIIF or UV community you might have seen our call for inspiration for 'UV IIIF transcription search design': Have you seen any notable versions of IIIF viewers that display and / or search transcribed (or translated, etc) text? Please add a screenshot and notes to a new slide on our working doc UV IIIF transcription search UX - and thank you to people who've already shared some links and ideas!

V&A visit

The V&A Museum's Digital Media team have been doing interesting things with IIIF for a number of years, so we organised a meetup between the British Library's UV team and V&A digital folk working with IIIF once our team was complete. In April we went over to the V&A to share our experiences and discuss potential ways to collaborate, like sharing documentation for getting started with the UV. Our thanks to Richard Palmer for hosting, Hussain Ali, Luca Carini and Meaghan Curry for sharing their work and ideas.

The British Library and V&A teams on the grass in the V&A's South Kensington courtyard

How can you help?

We - particularly Mia, Erin and Lanie - are keen to work on the viewer's usability (UX) and accessibility. What features are missing compared to other viewers? What tweaks can we make to the spatial grouping and labels for different functions to make them clearer and more consistent? You can get in touch via [email protected], or post on the IIIF or Universal Viewer Slacks (join the Universal Viewer Slack; join the IIIF Slack).

The British Library is continuing to recover from last year’s cyber-attack. While our teams work to restore our services safely and securely, one of our goals in the Digital Research Team is to get some of the information from our currently inaccessible web pages into an easily readable and shareable format. We’ll be sharing these pages via blog posts here, with information recovered from the Wayback Machine, a fantastic initiative of the Internet Archive.  

The next page in this series is all about the student projects that came out of our Computing for Cultural Heritage project with the National Archives and Birkbeck University. This student project page was captured by the Wayback Machine on 7 June 2023.  

 

Computing for Cultural Heritage Student Projects

This page provides abstracts for a selection of student projects undertaken as part of a one-year part-time Postgraduate Certificate (PGCert), Computing for Cultural Heritage, co-developed by British Library, National Archives and Birkbeck University and funded by the Institute of Coding as part of a £4.8 million University skills drive.

“I have gone from not being able to print 'hello' in Python to writing some relatively complex programs and having a much greater understanding of data science and how it is applicable to my work."

- Jessica Green  

Key points

• Aim of the trial was to provide professionals working in the cultural heritage sector with an understanding of basic programming and computational analytic tools to support them in their daily work 
• During the Autumn & Spring terms (October 2019-April 2020), 12 staff members from British Library and 8 staff staff members from The National Archives completed two new trial modules at Birkbeck University: Demystifying computing for heritage professionals and Work-based Project 
• Birkbeck University have now launched the Applied Data Science (Postgraduate Certificate) based on the outcomes of the trial

Student Projects

 

Transforming Physical Labels into Digital References 

Sotirios Alpanis, British Library
This project aims to use computing to convert data collected during the preparation of archive material for digitisation into a tool that can verify and validate image captures, and subsequently label them. This will take as its input physical information about each document being digitised, perform and facilitate a series of validations throughout image capture and quality assurance and result in an xml file containing a map of physical labels to digital files. The project will take place within the British Library/Qatar Foundation Partnership (BL/QFP), which is digitising archive material for display on the QDL.qa.  

Enhancing national thesis metadata with persistent identifiers

Jenny Basford, British Library 
Working with data from ISNI (International Standard Name Identifier) Agency and EThOS (Electronic Theses Online Service), both based at the British Library, I intend to enhance the metadata of both databases by identifying doctoral supervisors in thesis metadata and matching these data with ISNI holdings. This work will also feed into the European-funded FREYA project, which is concerned with the use of a wide variety of persistent identifiers across the research landscape to improve openness in research culture and infrastructure through Linked Data applications.

A software tool to support the social media activities of the Unlocking Our Sound Heritage Project

Lucia Cavorsi, British Library
Video
I would like to design a software tool able to flag forthcoming anniversaries, by comparing all the dates present in SAMI (sound and moving image catalogue – Sound Archive) with the current date. The aim of this tool is to suggest potential content for the Sound Archive’s social media posts. Useful dates in SAMI which could be matched with the current date and provide material for tweets are: birth and death dates of performers or authors, radio programme broadcast dates, recording dates).  I would like this tool to also match the subjects currently present in SAMI with the subjects featured in the list of anniversaries 2020 which the social media team uses. For example anniversaries like ‘International HIV day’, ‘International day of Lesbian visibility’ etc.  A windows pop up message will be designed for anniversaries notifications on the day.  If time permits, it would be convenient to also analyse what hashtags have been used over last year by the people who are followed by or follow the Sound Archive Twitter account. By extracting a list of these hashtags further, and more sound related, anniversaries could be added to the list of anniversaries currently used by the UOSH’s social media team.

Computing Cholera: Topic modelling the catalogue entries of the General Board of Health

Christopher Day, The National Archives
Blog / Other
The correspondence of the General Board of Health (1848–1871) documents the work of a body set up to deal with cholera epidemics in a period where some English homes were so filthy as to be described as “mere pigholes not fit for human beings”. Individual descriptions for each of these over 89,000 letters are available on Discovery, The National Archives (UK)’s catalogue. Now, some 170 years later, access to the letters themselves has been disrupted by another epidemic, COVID-19. This paper examines how data science can be used to repurpose archival catalogue descriptions, initially created to enhance the ‘human findability’ of records (and favoured by many UK archives due to high digitisation costs), for large-scale computational analysis. The records of the General Board will be used as a case study: their catalogue descriptions topic modelled using a latent Dirichlet allocation model, visualised, and analysed – giving an insight into how new sanitary regulations were negotiated with a divided public during an epidemic. The paper then explores the validity of using the descriptions of historical sources as a source in their own right; and asks how, during a time of restricted archival access, metadata can be used to continue research.

An Automated Text Extraction Tool for Use on Digitised Maps

Nicholas Dykes, British Library
Blog / Video
Researchers of history often have difficulty geo-locating historical place names in Africa. I would like to apply automated transcription techniques to a digitised archive of historical maps of Africa to create a resource that will allow users to search for text, and discover where, and on which maps that text can be found. This will enable identification and analysis both of historical place names and of other text, such as topographical descriptions. I propose to develop a software tool in Python that will send images stored locally to the Google Vision API, and retrieve and process a response for each image, consisting of a JSON file containing the text found, pixel coordinate bounding boxes for each instance of text, and a confidence score. The tool will also create a copy of each image with the text instances highlighted. I will experiment with the parameters of the API in order to achieve the most accurate results.  I will incorporate a routine that will store each related JSON file and highlighted image together in a separate folder for each map image, and create an Excel spreadsheet containing text results, confidence scores, links to relevant image folders, and hyperlinks to high-res images hosted on the BL website. The spreadsheet and subfolders will then be packaged together into a single downloadable resource.  The finished software tool will have the capability to create a similar resource of interlinked spreadsheet and subfolders from any batch of images.

Reconstituting a Deconstructed Dataset using Python and SQLite

Alex Green, The National Archives
Video
For this project I will rebuild a database and establish the referential integrity of the data from CSV files using Python and SQLite. To do this I will need to study the data, read the documentation, draw an entity relationship diagram and learn more about relational databases. I want to enable users to query the data as they would have been able to in the past. I will then make the code reusable so it can be used to rebuild other databases, testing it with a further two datasets in CSV form. As an additional challenge, I plan to rearrange the data to meet the principles of ‘tidy data’ to aid data analysis.

PIMMS: Developing a Model Pre-Ingest Metadata Management System at the British Library

Jessica Green, British Library
GitHub / Video
I am proposing a solution to analysing and preparing for ingest a vast amount of ‘legacy’ BL digitised content into the future Digital Asset Management System (DAMPS). This involves building a prototype for a SQL database to aggregate metadata about digitised content and preparing for SIP creation. In addition, I will write basic queries to aid in our ongoing analysis about these TIFF files, including planning for storage, copyright, digital preservation and duplicate analysis. I will use Python to import sample metadata from BL sources like SharePoint, Excel and BL catalogues – currently used for analysis of ‘live’ and ‘legacy’ digitised BL collections. There is at least 1 PB of digitised content on the BL networks alone, as well as on external media such as hard-drives and CDs. We plan to only ingest one copy of each digitised TIFF file set and need to ensure that the metadata is accurate and up-to-date at the point of ingest. This database, the Pre-Ingest Metadata Management System (PIMMS), could serve as a central metadata repository for legacy digitised BL collections until then. I look forward to using Python and SQL, as well as drawing on the coding skills from others, to make these processes more efficient and effective going forward.

Exploring, cleaning and visualising catalogue metadata

Alex Hailey, British Library
Blog / Video
Working with catalogue metadata for the India Office Records (IOR) I will undertake three tasks: 1) converting c430,000 IOR/E index entries to descriptions within the relevant volume entries; 2) producing an SQL database for 46,500 IOR/P descriptions, allowing enhanced search when compared with the BL catalogue; and 3) creating Python scripts for searching, analysis and visualisation, to be demonstrated on dataset(s) and delivered through Jupyter Notebooks.

Automatic generation of unique reference numbers for structured archival data.

Graham Jevon, British Library
Blog / Video / GitHub
The British Library’s Endangered Archives Programme (EAP) funds the digital preservation of endangered archival material around the world. Third party researchers digitise material and send the content to the British Library. This is accompanied by an Excel spreadsheet containing metadata that describes the digitised content. EAP’s main task is to clean, validate, and enhance the metadata prior to ingesting it into the Library’s cataloguing system (IAMS). One of these tasks is the creation of unique catalogue reference numbers for each record (each row of data on the spreadsheet). This is a predominantly manual process that is potentially time consuming and subject to human inputting errors. This project seeks to solve this problem. The intention is to create a Windows executable program that will enable users to upload a csv file, enter a prefix, and then click generate. The instant result will be an export of a new csv file, which contains the data from the original csv file plus automatically generated catalogue reference numbers. These reference numbers are not random. They are structured in accordance with an ordered archival hierarchy. The program will include additional flexibility to account for several variables, including language encoding, computational efficiency, data validation, and wider re-use beyond EAP and the British Library.

Automating Metadata Extraction in Born Digital Processing

Callum McKean, British Library
Video
To automate the metadata extraction section of the Library’s current work-flow for born-digital processing using Python, then interrogate and collate information in new ways using the SQLite module.

Analysis of peak customer interactions with Reference staff at the British Library: a software solution

Jaimee McRoberts, British Library
Video
The British Library, facing on-going budget constraints, has a need to efficiently deploy Reference Services staff during peak periods of demand. The service would benefit from analysis of existing statistical data recording the timestamp of each customer interaction at a Reference Desk. In order to do this, a software solution is required to extract, analyse, and output the necessary data. This project report demonstrates a solution utilising Python alongside the pandas library which has successfully achieved the required data analysis.

Enhancing the data in the Manorial Documents Register (MDR) and making it more accessible

Elisabeth Novitski, The National Archives
Video
To develop computer scripts that will take the data from the existing separate and inconsistently formatted files and merge them into a consistent and organised dataset. This data will be loaded into the Manorial Documents Register (MDR) and National Register of Archives (NRA) to provide the user with improved search ability and access to the manorial document information.

Automating data analysis for collection care research at The National Archives: spectral and textual data

Lucia Pereira Pardo, The National Archives
The day-to-day work of a conservation scientist working for the care of an archival collection involves acquiring experimental data from the varied range of materials present in the physical records (inks, pigments, dyes, binding media, paper, parchment, photographs, textiles, degradation and restoration products, among others). To this end, we use multiple and complementary analytical and testing techniques, such as X-ray fluorescence (XRF), Fourier Transform Infrared (FTIR) and Fibre Optic Reflectance spectroscopies (FORS), multispectral imaging (MSI), colour and gloss measurements, microfading (MFT) and other accelerated ageing tests.  The outcome of these analyses is a heterogeneous and often large dataset, which can be challenging and time-consuming to process and analyse. Therefore, the objective of this project is to automate these tasks when possible, or at least to apply computing techniques to optimise the time and efforts invested in routine operations, so that resources are freed for actual research and more specialised and creative tasks dealing with the interpretation of the results.

Improving efficiencies in content development through batch processing and the automation of workloads

Harriet Roden, British Library
Video
With the purpose to support and enrich the curriculum, the British Library’s Digital Learning team produces large-scale content packages for online learners through individual projects. Due to their reliance on other internal teams within the workflow for content delivery, a substantial amount of resource is spent on routine tasks to duplicate collection metadata across various databases. In order to reduce inefficiencies, increase productivity and improve reliability, my project aimed to alleviate pressures across the workflow through workload automation, through four separate phases.

The Botish Library: building a poetry printing machine with Python

Giulia Carla Rossi, British Library
Blog / Video
This project aims to build a poetry printing machine, as a creative output that unites traditional content, new media and Python. The poems will be sourced from the British Library Digitised Books dataset collection, available under Public Domain Mark; I will sort through the datasets and identify which titles can be categorised as poetry using Python. I will then create a new dataset comprising these poetry books and relative metadata, which will then be connected to the printer with a Python script. The poetry printing machine will print randomized poems from this new dataset, together with some metadata (e.g. poem title, book title, author and shelfmark ID) that will allow users to easily identify the book.

Automating data entry in the UOSH Tracking Database

Chris Weaver, British Library
The proposed software solution is the creation of a Python script (to feature as a module in a larger script) to extract data from a web-based tool (either via obtaining data in JSON format via the sites' API or accessing the database powering the site directly). The data obtained is then formatted and inserted into corresponding fields in a Microsoft SQL Server database.

Final Module

Following the completion of the trial, participants had the opportunity to complete their PGCert in Applied Data Science by attending the final module, Analytic Tools for Information Professionals, which was part of the official course launched last autumn. We followed up with some of the participants to hear more about their experience of the full course:

“The third and final module of the computing for cultural heritage course was not only fascinating and enjoyable, it was also really pertinent to my job and I was immediately able to put the skills I learned into practice.  

The majority of the third module focussed on machine learning. We studied a number of different methods and one of these proved invaluable to the Agents of Enslavement research project I am currently leading. This project included a crowdsourcing task which asked the public to draw rectangles around four different types of newspaper advertisement. The purpose of the task was to use the coordinates of these rectangles to crop the images and create a dataset of adverts that can then be analysed for research purposes. To help ensure that no adverts were missed and to account for individual errors, each image was classified by five different people.  

One of my biggest technical challenges was to find a way of aggregating the rectangles drawn by five different people on a single page in order to calculate the rectangles of best fit. If each person only drew one rectangle, it was relatively easy for me to aggregate the results using the coding skills I had developed in the first two modules. I could simply find the average (or mean) of the five different classification attempts. But what if people identified several adverts and therefore drew multiple rectangles on a single page? For example, what if person one drew a rectangle around only one advert in the top left corner of the page; people two and three drew two rectangles on the same page, one in the top left and one in the top right; and people four and five drew rectangles around four adverts on the same page (one in each corner). How would I be able to create a piece of code that knew how to aggregate the coordinates of all the rectangles drawn in the top left and to separately aggregate the coordinates of all the rectangles drawn in the bottom right, and so on?  

One solution to this problem was to use an unsupervised machine learning method to cluster the coordinates before running the aggregation method. Much to my amazement, this worked perfectly and enabled me to successfully process the total of 92,218 rectangles that were drawn and create an aggregated dataset of more than 25,000 unique newspaper adverts.” 

-Graham Jevon, EAP Cataloguer; BL Endangered Archives Programme 

“The final module of the course was in some ways the most challenging — requiring a lot of us to dust off the statistics and algebra parts of our brain. However, I think, it was also the most powerful; revealing how machine learning approaches can help us to uncover hidden knowledge and patterns in a huge variety of different areas.  

Completing the course during COVID meant that collection access was limited, so I ended up completing a case study examining how generic tropes have evolved in science fiction across time using a dataset extracted from GoodReads. This work proved to be exceptionally useful in helping me to think about how computers understand language differently; and how we can leverage their ability to make statistical inferences in order to support our own, qualitative analyses. 

In my own collection area, working with born digital archives in Contemporary Archives and Manuscripts, we treat draft material — of novels, poems or anything else — as very important to understanding the creative process. I am excited to apply some of these techniques — particularly Unsupervised Machine Learning — to examine the hidden relationships between draft material in some of our creative archives. 

The course has provided many, many avenues of potential enquiry like this and I’m excited to see the projects that its graduates undertake across the Library.” 

- Callum McKean, Lead Curator, Digital; Contemporary British Collection

“I really enjoyed the Analytics Tools for Data Science module. As a data science novice, I came to the course with limited theoretical knowledge of how data science tools could be applied to answer research questions. The choice of using real-life data to solve queries specific to professionals in the cultural heritage sector was really appreciated as it made everyday applications of the tools and code more tangible. I can see now how curators’ expertise and specialised knowledge could be combined with tools for data analysis to further understanding of and meaningful research in their own collection area."

- Giulia Carla Rossi, Curator, Digital Publications; Contemporary British Collection

Please note this page was originally published in Feb 2021 and some of the resources, job titles and locations may now be out of date.

The British Library is continuing to recover from last year’s cyber-attack. While our teams work to restore our services safely and securely, one of our goals in the Digital Research Team is to get some of the information from our currently inaccessible web pages into an easily readable and shareable format. We’ll be sharing these pages via blog posts here, with information recovered from the Wayback Machine, a fantastic initiative of the Internet Archive.  

The second page in this series is a case study on the impact of our Digital Scholarship Training Programme, captured by the Wayback Machine on 3 October 2023. 

 

Graham Jevon: A Digital Transformation Story

'The Digital Scholarship Training Programme has introduced me to new software, opened my eyes to digital opportunities, provided inspiration for me to improve, and helped me attain new skills'

Key points

• Graham Jevon has been an active participant in the Digital Scholarship Training Programme
• Through gaining digital skills he has been able to build software to automate tricky processes
• Graham went on to become a Coleridge Fellowship scholar, putting these digital skills to good use!

Find out more on what Graham has been up to on his Staff Profile

Did you know? The Digital Scholarship Training Programme has been running since 2012, and creates opportunities for staff to develop necessary skills and knowledge to support emerging areas of modern scholarship.

The Digital Scholarship Training Programme

Since joining the library in 2018, the Digital Scholarship Training Programme has been integral to the trajectory of both my personal development and the working practices within my team.

The very first training course I attended at the library was the introduction to OpenRefine. The key thing that I took away from this course was not necessarily the skills to use the software, but simply understanding OpenRefine’s functionality and the possibilities the software offered for my team. This inspired me to spend time after the session devising a workflow that enhanced our cataloguing efficiency and accuracy, enabling me to create more detailed and accurate metadata in less time. With OpenRefine I created a semi-automated workflow that required the kind of logical thinking associated with computer programming, but without the need to understand a computer programming language.

 

Computing for Cultural Heritage

The use of this kind of logical thinking and the introduction to writing computational expressions within OpenRefine sparked an interest in me to learn a computing language such as Python. I started a free online Python introduction, but without much context to the course my attention quickly waned. When the Digital Scholarship Computing for Cultural Heritage course was announced I therefore jumped at the chance to apply. 

I went into the Computing for Cultural Heritage course hoping to learn skills that would enable me to solve cataloguing and administrative problems, skills that would help me process data in spreadsheets more efficiently and accurately. I had one particular problem in mind and I was able to address this problem in the project module of the course. For the project we had to design a software program. I created a program (known as ReG), which automatically generates structured catalogue references for archival collections. I was extremely pleased with the outcome of this project and this piece of software is something that my team now use in our day-to-day activities. An error-prone task that could take hours or days to complete manually in Excel now takes just a few seconds and is always 100% accurate.

This in itself was a great outcome of the course that met my hopes at the outset. But this course did so much more. I came away from the course with a completely new set of data science skills that I could build on and apply in other areas. For example, I recently created another piece of software that helps my team survey any digitisation data that we receive, to help us spot any errors or problems that need fixing.

 

 

The British Library Coleridge Research Fellowship

The data science skills were particularly instrumental in enabling me to apply successfully for the British Library’s Coleridge research fellowship. This research fellowship is partly a personal development scheme and it enabled me the opportunity to put my new data science skills into practice in a research environment (rather than simply using them in a cataloguing context). My previous academic research experience was based on traditional analogue methods. But for the Coleridge project I used crowdsourcing to extract data for analysis from two collections of newspapers.

The third and final Computing for Cultural Heritage module focussed on machine learning and I was able to apply these skills directly to the crowdsourcing project Agents of Enslavement. The first crowdsourcing task, for example, asked the public to draw rectangles around four specific types of newspaper advertisement. To help ensure that no adverts were missed and to account for individual errors, each image was classified by five different people. I therefore had to aggregate the results. Thanks to the new data science skills I had learned, I was able to write a Python script that used machine learning algorithms to aggregate 92,000 total rectangles drawn by the public into an aggregated dataset of 25,000 unique newspaper advertisements.

The OpenRefine and Computing for Cultural Heritage course are just two of the many digital scholarship training sessions that I have attended. But they perfectly illustrate the value of the Digital Scholarship Training Programme, which has introduced me to new software, opened my eyes to digital opportunities, provided inspiration for me to improve, and helped me attain new skills that I have been able to put into practice both for the benefit of myself and my team.

The British Library is continuing to recover from last year’s cyber-attack. While our teams work to restore our services safely and securely, one of our goals in the Digital Research Team is to get some of the information from our currently inaccessible web pages into an easily readable and shareable format. We’ll be sharing these pages via blog posts here, with information recovered from the Wayback Machine, a fantastic initiative of the Internet Archive.  

The first page in this series is about our Digital Scholarship Training Programme, captured by the Wayback Machine on 27 September 2023.  

 

The Digital Scholarship Training Programme 

The Digital Scholarship Training Programme has been running since 2012, and creates opportunities for staff to develop necessary skills and knowledge to support emerging areas of modern scholarship. 

 

About 

This internal and bespoke staff training programme is one of the cornerstones of the Digital Curator Team’s work at the British Library. Running since 2012, it provides colleagues with the space and opportunity to delve into and explore all that digital content and new technologies have to offer in the research domain today. The Digital Curator team oversees the design and delivery of roughly 50-60 training events a year. Since its inception, well over a thousand individual staff members have come through the programme, on average attending three or more courses each and the Library has seen a steep change in its capacity to support innovative digital research.  

 

Objectives 

1. Staff are familiar and conversant with the foundational concepts, methods and tools of digital scholarship. 
2. Staff are empowered to innovate. 
3. Collaborative digital initiatives flourish across subject areas within the Library as well as externally.
4. Our internal capacity for training and skill-sharing in digital scholarship are a shared responsibility across the Library. 

 

The Programme 

What's it all about? 

To celebrate our ten year anniversary, we created a series of video testimonials from the people behind the Training Programme - coordinators, instructors, and attendees. Click 'Watch on YouTube' to view the whole series of videos.

 

Nora McGregor, Digital Curator, gives a presentation all about the Digital Scholarship Training Programme - where it started, where it's going and what it hopes to accomplish. 

 

Courses 

As digital research methods have changed overtime, so too have course topics and content. Today's full course catalogue reflects this through a diversity of topics from cleaning up data, digital storytelling, to command line programming and geo-referencing. 

Courses range from half-days to full-day workshops for no more than 15 attendees at a time and are taught mainly by staff members but also external trainers where necessary. Example courses include: 

105 Crowdsourcing in Libraries, Museums and Cultural Heritage Institutions 

107 Data Visualisation for Cultural Heritage Collections 

109 Information Integration: Mash-ups, API’s and Linked Data 

118 Cleaning up Data 

 

Hack & Yacks 

We host a monthly “Hack & Yack” to run alongside the more formal training programme. During these two-hour self-paced casual meet-ups, open to all staff, the group works through a variety of online tutorials on a particular digital topic. Example sessions include: 

Transcribing Handwritten Text 

Transforming XML with XSLT 

Interactive writing platforms 

 

Digital Scholarship Reading Group 

The Digital Scholarship Reading Group holds informal discussions on the first Tuesday of each month. Each month we discuss an article, conference, podcast or video related to digital scholarship. It's a great way to keep up with new ideas or reality check trends in digital scholarship (including the digital humanities). We welcome people from any department in the Library, and take suggestions for topics that are particularly relevant to diverse teams or disciplines. 

Curious about what we cover? Check out this previous blog post that cover the last five years of our Reading Group.

 

21st Century Curatorship Talk Series 

The Digital Scholarship team hosts the 21st Century Curatorship Programme (C21st), a series of professional development talks and seminars, open to all staff, providing a forum for keeping up with new developments and emerging technologies in scholarship, libraries and cultural heritage. 
 

What’s new? 

In 2019, the British Library and partners Birkbeck University and The National Archives were awarded £222,420 in funding by the Institute of Coding (IoC) to co-develop a one-year part-time postgraduate Certificate (PGCert), Computing for Cultural Heritage, as part of a £4.8 million University skills drive. The new course aims to provide working professionals, particularly across the GLAM sector (Galleries, Libraries, Archives and Museums), with an understanding of basic programming, analytic tools and computing environments to support them in their daily work.  

 

Further information 

For more information on the Training Programme's most recent year, including our performance numbers and topics covered by the training, please see our full screen, interactive inforgraphic.  

Please also see our two conference papers from Digital Humanities 2013 and Digital Humanities 2016 for more details on how the Training Programme was established. Any queries about this project can be directed to [email protected].