Digital scholarship blog

This guest post is by Alex Hailey, Curator of Modern Archives and Manuscripts. He's on Twitter as @ajrhailey.

In late 2019 I was lucky enough to join BL and National Archives staff to trial a PG Certificate in Computing for Cultural Heritage at Birkbeck. The course provided an introduction to programming with Python, the basics of SQL, and using the two to work with data. Fellow attendees Graham, Nick, Chris and Giulia have written about their work previously, and I am going to briefly introduce one of my project tasks addressing issues with legacy metadata within the India Office Records.

The original data

The IOR/E/4 Correspondence with India series consists of 1,112 volumes dating from 1703-1858: four series of letters received by the East India Company (EIC) Court of Directors from the administration in India, and four series of dispatches sent to India. Catalogue entries for these volumes contain only basic information – title, dates, language, reference and former references – and subject, name and place access to the dispatches is provided through 72 index volumes (reference IOR/Z/E/4), which contain around 430,000 entries.

Sample catalogue record of an index entry, IOR/Z/E/4/42/P133

The original indexes were produced from 1901-1929 by staff of the Secretarial Bureau, led by indexing pioneer Mary Petherbridge; my colleague Antonia Moon has written about Petherbridge’s work in a previous post. When these indexes were converted to the catalogue in the early 2010s, entries within the index volumes were entered as child or sub-items of the index volumes themselves, with information on the related correspondence volumes entered into the free-text Related material field, as shown in the image above.

Problem and solution

This approach has caused some issues. Firstly, users attempting to order the related correspondence regularly end up trying to place an order for an index volume instead, which is frustrating. Secondly, it makes it practically impossible to determine the whole contents of a particular volume in a quick and easy manner, which frustrates access and use.

Manually working through 430,000 entries to group the entries by volume would be an impossible task, but I was able to use Python and a library called Pandas, which has a number of useful features for examining and manipulating catalogue data: methods for reading and writing data from multiple sources, flexible reshaping of datasets, and methods for aggregation, indexing, splitting and replacing strings, including regular expressions.

Using Pandas I was able to separate information in the Related material field, restructure the data so that each instance of an index entry formed an individual record, and then group these by volume and further arrange them alphabetically or by page order.

Index entries for reference IOR/Z/E/4/42/P133 split into separate records

Outputs and analysis

Examining these outputs gave us new insights into the data. We now know that the indexes cover 230 volumes of the dispatches only. We were also able to identify incomplete references originally recorded in the Related material field, as well as what appear to be keying errors (references which fall outside of the range of the dispatches series). We can now follow these up and correct errors in the catalogue which were previously unknown.

Comparing the data at volume level arranged alphabetically and by page order, we could appreciate just how much depth there was to the index. Traditional indexes are written with a lot of information redundancy, which isn’t immediately apparent until you group the entries according to their location within a particular volume:

Example of index entries arranged by page order

After discussion with the IOR team we have decided to take the alphabetically arranged data and import it to the archives catalogue, so that users selecting a dispatches volume are presented with the relevant index entries immediately.

The original dataset and derived datasets have been uploaded to the Library’s research repository where they are available for download and reuse under a CC0 licence.

To enable further analysis of the index data I have also tried my hand at creating a Jupyter Notebook to use with the derived data. This is intended to introduce colleagues to using Notebooks, Python and the Pandas library to examine catalogue metadata, conducting basic queries, producing a visualisation and exporting subsets for further investigation.

Wordcloud based on terms contained in the IOR/Z/E/4 data, generated within the Jupyter Notebook.

My Birkbeck project also included work to create place and institution authority files for the Proceedings of the Governments of India series using keyword extraction with existing catalogue metadata, and this will be discussed in a future post.

Huge thanks must go to Nora McGregor, Jo Pugh and the folks at Birkbeck Department of Computer Science for developing the course and providing us with this opportunity; Antonia Moon and the IOR team for helpful discussions about the IOR data; and the rest of the cohort for moral support when the computer just wouldn’t behave.

Alex Hailey

Curator of Modern Archives and Manuscripts

Looking for entries now!

Nominate an existing British Library staff member or a team that has done something exciting, innovative and cool with the British Library’s digital collections or data.

The 2020 British Library Labs Staff Award, now in its fifth year, gives recognition to current British Library staff who have created something brilliant using the Library’s digital collections or data.

Perhaps you know of a project that developed new forms of knowledge, or an activity that delivered commercial value to the library. Did the person or team create an artistic work that inspired, stimulated, amazed and provoked? Do you know of a project developed by the Library where quality learning experiences were generated using the Library’s digital content? 

You may nominate a current member of British Library staff, a team, or yourself (if you are a member of staff), for the Staff Award using this form.

The deadline for submission is NOON (GMT), Monday 30 November 2020.

Nominees will be highlighted on Tuesday 15 December 2020 at the online British Library Labs Annual Symposium where some (winners and runners-up) will also be asked to talk about their projects (everyone is welcome to attend, you just need to register).

You can see the projects submitted by members of staff and public for the awards in our online archive.

In 2019, last year's winner focused on the brilliant work of the Imaging Team for the 'Qatar Foundation Partnership Project Hack Days', which were sessions organised for the team to experiment with the Library's digital collections. 

The runner-up for the BL Labs Staff Award in 2019 was the Heritage Made Digital team and their social media campaign to promote the British Library's digital collections one language a week from letters 'A' to 'U' #AToUnknown).

In the public Awards, last year's winners (2019) drew attention to artistic, research, teaching & learning, and community activities that used our data and / or digital collections.

British Library Labs is a project within the Digital Scholarship department at the British Library that supports and inspires the use of the Library's digital collections and data in exciting and innovative ways. It was previously funded by the Andrew W. Mellon Foundation and is now solely funded by the British Library.

If you have any questions, please contact us at [email protected].

Visualising the journey of a manuscript’s creation

Working for the Qatar Digital Library (QDL), I recently catalogued British Library oriental manuscript 2361, a musical compendium copied in Mughal India during the reign of Aurangzeb (1618-1707; ruled from 1658). The QDL is a British Library-Qatar Foundation collaborative project to digitise and share Gulf-related archival records, maps and audio recordings as well as Arabic scientific manuscripts.

Figure 1: Equestrian portrait of Aurangzeb. Mughal, c. 1660-70. British Library, Johnson Album, 3.4. Public domain.

The colophons to Or. 2361 fourteen texts contain an unusually large – but jumbled-up – quantity of information about the places and dates it was copied and checked, revealing that it was largely created during a journey taken by the imperial court in 1663.

Figure 2: Colophon to the copy of Kitāb al-madkhal fī al-mūsīqī by al-Fārābī, transcribed in Delhi, 3 Jumādá I, 1073 hijrī/14 December 1662 CE, and checked in Lahore, 22 Rajab 1073/2 March 1663. Or. 2361, f. 240r.

Seeking to make sense of the mass of bibliographic information and unpick the narrative of the manuscript’s creation, I recorded all this data in a spreadsheet. This helped to clarify some patterns- but wasn’t fun to look at! To accompany an Asian and African Studies blog post, I wanted to find an interactive digital tool to develop the visual and spatial aspects of the story and convey the landscapes and distances experienced by the manuscript’s scribes and patron during its mobile production.

Figure 3: Dull but useful spreadsheet of copy data for Or. 2361.

Many fascinating digital tools can present large datasets, including map co-ordinates. However, I needed to retell a linear, progressive narrative with fewer data points. Inspired by a QNF-BL colleague’s work on Geoffrey Prior’s trip to Muscat, I settled on StoryMap, one of an expanding suite of open-source reporting, data management, research, and storytelling tools developed by Knight Lab at Northwestern University, USA.

StoryMap: Easy but fiddly

Requiring no coding ability, the back-end of this free, easy-to-use tool resembles PowerPoint. The user creates a series of slides to which text, images, captions and copyright information can be added. Links to further online media, such as the millions of images published on the QDL, can easily be added.

Figure 4: Back-end view of StoryMap's authoring tool.

The basic incarnation of StoryMap is accessed via an author interface which is intuitive and clear, but has its quirks. Slide layouts can’t be varied, and image manipulation must be completed pre-upload, which can get fiddly. Text was faint unless entirely in bold, especially against a backdrop image. A bug randomly rendered bits of uploaded text as hyperlinks, whereas intentional hyperlinks are not obvious.

The mapping function

StoryMap’s most interesting feature is an interactive map that uses OpenStreetMap data. Locations are inputted as co-ordinates, or manually by searching for a place-name or dropping a pin. This geographical data links together to produce an overview map summarised on the opening slide, with subsequent views zooming to successive locations in the journey.

Figure 5: StoryMap summary preview showing all location points plotted.

I had to add location data manually as the co-ordinates input function didn’t work. Only one of the various map styles suited the historical subject-matter; however its modern street layout felt contradictory. The ‘ideal’ map – structured with global co-ordinates but correct for a specific historical moment – probably doesn’t exist (one for the next project?).

Figure 6: StoryMap's modern street layout implies New Delhi existed in 1663...

With clearly signposted advanced guidance, support forum, and a link to a GitHub repository, more technically-minded users could take StoryMap to the next level, not least in importing custom maps via Mapbox. Alternative platforms such as Esri’s Classic Story Maps can of course also be explored.

However, for many users, Knight Lab StoryMap’s appeal will lie in its ease of usage and accessibility; it produces polished, engaging outputs quickly with a bare minimum of technical input and is easy to embed in web-text or social media. Thanks to Knight Lab for producing this free tool!

See the finished StoryMap, A Mughal musical miscellany: The journey of Or. 2361.

This is a guest post by Jenny Norton-Wright, Arabic Scientific Manuscripts Curator from the British Library Qatar Foundation Partnership. You can follow the British Library Qatar Foundation Partnership on Twitter at @BLQatar.

The sixth BL Labs Public Awards 2020 formally recognises outstanding and innovative work that has been carried out using the British Library’s data and / or digital collections by researchers, artists, entrepreneurs, educators, students and the general public.

The closing date for entering the Public Awards is NOON GMT on Monday 30 November 2020 and you can submit your entry any time up to then.

Please help us spread the word! We want to encourage any one interested to submit over the next few months, who knows, you could even win fame and glory, priceless! We really hope to have another year of fantastic projects to showcase at our annual online awards symposium on the 15 December 2020 (which is open for registration too), inspired by our digital collections and data!

This year, BL Labs is commending work in four key areas that have used or been inspired by our digital collections and data:

• Research - A project or activity that shows the development of new knowledge, research methods, or tools.
• Artistic - An artistic or creative endeavour that inspires, stimulates, amazes and provokes.
• Educational - Quality learning experiences created for learners of any age and ability that use the Library's digital content.
• Community - Work that has been created by an individual or group in a community.

What kind of projects are we looking for this year?

Whilst we are really happy for you to submit your work on any subject that uses our digital collections, in this significant year, we are particularly interested in entries that may have a focus on anti-racist work or projects about lock down / global pandemic. We are also curious and keen to have submissions that have used Jupyter Notebooks to carry out computational work on our digital collections and data.

After the submission deadline has passed, entries will be shortlisted and selected entrants will be notified via email by midnight on Friday 4th December 2020. 

A prize of £150 in British Library online vouchers will be awarded to the winner and £50 in the same format to the runner up in each Awards category at the Symposium. Of course if you enter, it will be at least a chance to showcase your work to a wide audience and in the past this has often resulted in major collaborations.

The talent of the BL Labs Awards winners and runners up over the last five years has led to the production of remarkable and varied collection of innovative projects described in our 'Digital Projects Archive'. In 2019, the Awards commended work in four main categories – Research, Artistic, Community and Educational:

BL  Labs Award Winners for 2019

• Research (2019) Winner: Full-Text search of Early Music Prints Online (F-TEMPO) by Tim Crawford, Goldsmiths, University of London
• Artistic (2019) Winner: Emerging Formats: Discovering and Collecting Contemporary British Interactive Fiction by Lynda Clark
• Community Commendation (2019): John Faucit Saville and the theatres of the East Midlands Circuit - by Lesley Phillips
• Teaching and Learning / Educational (2019) Winner: The Other Voice - RCA - Innovations in sound and art by Masters' students from the Royal College of Art, submitted by Dr Matt Lewis, Tutor of Digital Direction and Dr Eleanor Dare, Reader of Digital Media both at the School of Communication, at the Royal College of Art and Mary Stewart Curator, Oral History and Deputy Director of National Library

For further detailed information, please visit BL Labs Public Awards 2020, or contact us at [email protected] if you have a specific query.

Posted by Mahendra Mahey, Manager of British Library Labs.

This guest blog post is by Michael St John-McAlister, Western Manuscripts Cataloguing Manager at the British Library.

The coronavirus lockdown is a good opportunity to carry out some of those house-keeping tasks that would never normally get done (and I do not mean re-grouting the bathroom). Anticipating that we would be sent home and knowing I would be limited in the work I could do at home, I asked IT to download all the name authorities in our archives and manuscripts cataloguing system (all 324,106 of them) into a spreadsheet that I would be able to work on at home.

Working through the names, looking for duplicate records, badly-formed names, and typos, my eye was caught by the variety of epithets that have been used over 267 years of manuscripts cataloguing.

For the uninitiated, an epithet is part of a name authority or index term, in the form of a short descriptive label, used to help distinguish people of the same name. Imagine you are writing a biography of a John Smith. You search the Explore Archives and Manuscripts catalogue for any relevant primary sources, only to find three entries for Smith, John, 1800-1870. How would you know which John Smith’s letters and diaries to call up for your research? (Humour me: let us assume our three Smiths all have the same vital dates, unlikely I know, and that the papers are not fully catalogued so the catalogue descriptions of the papers themselves cannot help you decide as they would normally).

Now imagine your catalogue search for John Smith turned up the following entries instead:

Smith, John, 1810-1880, baker

Smith, John, 1810-1880, butcher

Smith, John, 1810-1880, candlestick maker

Instantly, you can see which of the three John Smiths is relevant to your ground-breaking research into the history of candlestick making in the West Riding in the early Victorian era.

The epithet is one element of a well-formed index term and it tends to be a position in life (King of Jordan; Queen of Great Britain and Ireland), a former or alternative name (née Booth; pseudonym ‘Jane Duncan’), a career or occupation (soldier; writer), or a relationship to another person (husband of Rebecca West; son of Henry VII).

Scrolling through the spreadsheet, in amongst the soldiers, writers, composers, politicians, Earls of this, and Princesses of that, I stumbled across a fascinating array of epithets, some obvious, some less so.

There are plenty of examples of the perhaps slightly everyday, but important all the same: bricklayer; plumber; glazier; carpenter. As well as the trades common to us today, some of the trades used as epithets seem very much of their times: button-maker; coach and harness maker; dealer in fancy goods; butterman; copperplate printer; hackney coachman.

Those from the edges of law-abiding society loom large, with people described as burglar and prisoner (presumably the former led to his becoming the latter), convict, assassin, murderer, pickpocket, forger, felon, regicide, and rioter. There are even 50 pirate’s wives in the catalogue (but only seven pirates!). The victims of conflict and persecution also crop up, including prisoner of war, martyr, and galley slave, as well as, occasionally, their tormentors (inquisitor, head jailer, arms dealer).

Some of the epithets have a distinct air of mystery about them (codebreaker; conspirator; spy; alchemist; child prodigy; fugitive; renegade priest; hermit; recluse; mystic; secret agent; intercept operator; dream interpreter) whilst others exude a certain exoticism or loucheness: casino owner; dance band leader; acrobat; mesmerist; jazz poet; pearl fisher; showman; diamond tycoon; charioteer.

Many of the epithets relate to services provided to others. Where would the great and the good be without people to drive them around, manage their affairs, assist in their work, take their letters, make their tea, cook their food, and treat them when they fall ill. So, Marcel Proust’s chauffeur, Charlie Chaplin’s business manager, Gustav Holsts’s many amanuenses, Laurence Olivier’s secretary, Virginia Woolf’s charwoman, as well as her cook, and HG Wells’s physician all make appearances in the catalogue.

Then there are the epithets which are less than useful and do not really enlighten us about their subjects: appraiser (of what?); connoisseur (ditto); purple dyer (why only purple?); political adventurer; official. The less said about the usefulness, or otherwise, of epithets such as Mrs, widow, Mr Secretary, and Libyan the better.  Some fall into the ‘What is it?’ category: coastwaiter (and landwaiter, for that matter); pancratiast; paroemiographer; trouvère.*

Another interesting category contains epithets of people with more than one string to their bow. One’s mind boggles at the career path of the ‘music scribe and spy’, or the ‘inn-keeper, gunner, and writer on mathematics’; is awed by the variety of skills of the ‘composer and physician’; marvels at the multi-talented ‘army officer, footballer, and Conservative politician’; and wonders what occurred in someone’s life to earn them the epithet ‘coach-painter and would-be assassin’.

As we have discovered, an epithet can help identify individuals, thus making the reader’s life easier, but if all else fails, and it is not possible to say who someone is, you can always say who they are not. Hence one of our manuscripts cataloguing forbears leaving us with Barry, Garrett; not Garrett Barry of Lisgriffin, county Cork as an index term.

• a type of Customs officer; ditto; a participant in a boxing or wrestling contest, esp. in ancient Greece; a writer or collector of proverbs; a medieval epic poet.

This guest blog post is by Michael St John-McAlister, Western Manuscripts Cataloguing Manager at the British Library.

Posted on behalf of Tim Crawford, Professorial Research Fellow in Computational Musicology at Goldsmiths, University of London and BL Labs Research Award winner for 2019 by Mahendra Mahey, Manager of BL Labs.

Introducing F-TEMPO

Early music printing

Music printing, introduced in the later 15th century, enabled the dissemination of the greatest music of the age, which until that time was the exclusive preserve of royal and aristocratic courts or the Church. A vast repertory of all kinds of music is preserved in these prints, and they became the main conduit for the spread of the reputation and influence of the great composers of the Renaissance and early Baroque periods, such as Josquin, Lassus, Palestrina, Marenzio and Monteverdi. As this music became accessible to the increasingly well-heeled merchant classes, entirely new cultural networks of taste and transmission became established and can be traced in the patterns of survival of these printed sources.

Music historians have tended to neglect the analysis of these patterns in favour of a focus on a canon of ‘great works’ by ‘great composers’, with the consequence that there is a large sub-repertory of music that has not been seriously investigated or published in modern editions. By including this ‘hidden’ musical corpus, we could explore for the first time, for example, the networks of influence, distribution and fashion, and the effects on these of political, religious and social change over time.

Online resources of music and how to read them

Vast amounts of music, mostly audio tracks, are now available using services such as Spotify, iTunes or YouTube. Music is also available online in great quantity in the form of PDF files rendering page-images of either original musical documents or modern, computer-generated music notation. These are a surrogate for paper-based books used in traditional musicology, but offer few advantages beyond convenience. What they don’t allow is full-text search, unlike the text-based online materials which are increasingly the subject of ‘distant reading’ in the digital humanities.

With good score images, Optical Music Recognition (OMR) programs can sometimes produce useful scores from printed music of simple texture; however, in general, OMR output contains errors due to misrecognised symbols. The results often amount to musical gibberish, severely limiting the usefulness of OMR for creating large digital score collections. Our OMR program is Aruspix, which is highly reliable on good images, even when they have been digitised from microfilm.

Here is a screen-shot from Aruspix, showing part of the original page-image at the top, and the program’s best effort at recognising the 16th-century music notation below. It is not hard to see that, although the program does a pretty good job on the whole, there are not a few recognition errors. The program includes a graphical interface for correcting these, but we don’t make use of that for F-TEMPO for reasons of time – even a few seconds of correction per image would slow the whole process catastrophically.

The Aruspix user-interface

Finding what we want – error-tolerant encoding

Although OMR is far from perfect, online users are generally happy to use computer methods on large collections containing noise; this is the principle behind the searches in Google Books, which are based on Optical Character Recognition (OCR).

For F-TEMPO, from the output of the Aruspix OMR program, for each page of music, we extract a ‘string’ representing the pitch-name and octave for the sequence of notes. Since certain errors (especially wrong or missing clefs or accidentals) affect all subsequent notes, we encode the intervals between notes rather than the notes themselves, so that we can match transposed versions of the sequences or parts of them. We then use a simple alphabetic code to represent the intervals in the computer.

Here is an example of a few notes from a popular French chanson, showing our encoding method.

A few notes from a Crequillon chanson, and our encoding of the intervals

F-TEMPO in action

F-TEMPO uses state-of-the-art, scalable retrieval methods, providing rapid searches of almost 60,000 page-images for those similar to a query-page in less than a second. It successfully recovers matches when the query page is not complete, e.g. when page-breaks are different. Also, close non-identical matches, as between voice-parts of a polyphonic work in imitative style, are highly ranked in results; similarly, different works based on the same musical content are usually well-matched.

Here is a screen-shot from the demo interface to F-TEMPO. The ‘query’ image is on the left, and searches are done by hitting the ‘Enter’ or ‘Return’ key in the normal way. The list of results appears in the middle column, with the best match (usually the query page itself) highlighted and displayed on the right. As other results are selected, their images are displayed on the right. Users can upload their own images of 16th-century music that might be in the collection to serve as queries; we have found that even photos taken with a mobile phone work well. However, don’t expect coherent results if you upload other kinds of image!

F-Tempo-User Interface

The F-TEMPO web-site can be found at: http://f-tempo.org

Click on the ‘Demo’ button to try out the program for yourself.

What more can we do with F-TEMPO?

Using the full-text search methods enabled by F-TEMPO’s API we might begin to ask intriguing questions, such as:

• ‘How did certain pieces of music spread and become established favourites throughout Europe during the 16th century?’
• ‘How well is the relative popularity of such early-modern favourites reflected in modern recordings since the 1950s?’
• ‘How many unrecognised arrangements are there in the 16th-century repertory?’

In early testing we identified an instrumental ricercar as a wordless transcription of a Latin motet, hitherto unknown to musicology. As the collection grows, we are finding more such unexpected concordances, and can sometimes identify the composers of works labelled in some printed sources as by ‘Incertus’ (Uncertain). We have also uncovered some interesting conflicting attributions which could provoke interesting scholarly discussion.

Early Music Online and F-TEMPO

From the outset, this project has been based on the Early Music Online (EMO) collection, the result of a 2011 JISC-funded Rapid Digitisation project between the British Library and Royal Holloway, University of London. This digitised about 300 books of early printed music at the BL from archival microfilms, producing black-and-white images which have served as an excellent proof of concept for the development of F-TEMPO. The c.200 books judged suitable for our early methods in EMO contain about 32,000 pages of music, and form the basis for our resource.

The current version of F-TEMPO includes just under 30,000 more pages of early printed music from the Polish National Library, Warsaw, as well as a few thousand from the Bibliothèque nationale, Paris. We will soon be incorporating no fewer than a further half-a-million pages from the Bavarian State Library collection in Munich, as soon as we have run them through our automatic indexing system.

 (This work was funded for the past year by the JISC / British Academy Digital Humanities Research in the Humanities scheme. Thanks are due to David Lewis, Golnaz Badkobeh and Ryaan Ahmed for technical help and their many suggestions.)

EXPLORING THEATRE HISTORY WITH BRITISH LIBRARY PLAYBILLS AND NEWSPAPERS

Posted on behalf of Lesley Phillips, a former Derbyshire local studies librarian in the UK and BL Labs Community Commendation Award winner for 2019 by Mahendra Mahey, Manager of BL Labs.

Lesley explains how the British Library's digital collections of playbills and digtised newspapers enabled her to compile a detailed account of the career of the actor-manager John Faucit Saville in the East Midlands 1843-1855.

John Faucit Saville was born in Norwich in 1807, the son of two actors then performing with the Norwich Company as Mr and Mrs Faucit. His parents separated when he was 14 years old and just entering on his stage career. His mother, then a leading actress at Drury Lane, moved in with the celebrated actor William Farren, and continued to perform as Mrs Faucit, while his father became a manager and changed his surname to Saville (his real name).

Oxberry's Dramatic Biography (1825) records his father's grief:

On the evening that the fatal news [of his wife's desertion] reached him [Mr John Faucit] left the theatre and walked over the beach. His lips trembled and he was severely agitated. Many persons addressed him, but he broke from them and went to the house of a particular friend. The facts were then known only to himself. Though a man of temperate habits, he drank upwards of two bottles of wine without being visibly affected. He paced the room and seemed unconscious of the presence of anyone. To his friend's inquiries he made no reply. He once said “My heart is almost broke, but you will soon know why”.

(C.E. Oxberry (ed.) Oxberry's Dramatic Biography and Histrionic Anecdotes. Vol. III (1825) pp. 33-34, Memoir of William Farren)

Despite the rift between his parents, John Faucit Saville had all the advantages that famous friends and relatives could bring in the theatrical world, but during his time as an aspiring actor it soon became clear that he would never be a great star. In 1841 he began to put his energies into becoming a manager, like his father before him. He took a lease of Brighton Theatre in his wife's home town, but struggled to make a success of it.

Like the other managers of his day he was faced with a decline in the fashion for rational amusements and the rise of 'beer and circuses'. This did not deter him from making a further attempt at establishing a theatrical circuit. For this he came to the East Midlands and South Yorkshire, where the decline of the old circuit and the retirement of Thomas Manly had laid the field bare for a new man. Saville must surely have had great confidence in his own ability to be successful here, given that the old, experienced manager had begun to struggle.

Saville took on the ailing circuit, and soon discovered that he was forced to make compromises. He was careful to please the local authorities as to the respectability of his productions, and yet managed to provide more lowbrow entertainments to bring in the audiences. Even so, after a few years he was forced to reign in his ambitions and eventually reduce his circuit, and he even went back on tour as an itinerant actor from time to time to supplement his income. Saville's career had significant implications for the survival of some of the theatres of the East Midlands, as he lived through the final disintegration of the circuit.

Over the years, John Faucit Saville's acting career had taken him to Paris, Edinburgh, and Dublin, as well as many parts of England. Without the use of digital online resources it would be almost impossible to trace a career such as his, to explore his background, and bring together the details of his life and work.

Newspaper article from 29 January 1829 detailing the benefit performance for Mr Faucit entitled 'Clandestine Marriage' at the Theatre Royal Brighton

The digitised newspapers of the British Newspaper Archive https://www.britishnewspaperarchive.co.uk enabled me to uncover the Saville family origins in Bedford, and to follow John Faucit Saville's career from the heights of the London stage, to management at Brighton and then to the Midlands.

Newspaper article detailing benefit performance for Mr JF Saville at Theatre Royal Derby on Friday May 23, 1845, play entitled 'Don Caesar de Bazan' or 'Martina the Gypsy'

The dataset of playbills available to download from the British Library web site https://data.bl.uk/playbills/pb1.html enabled me to build up a detailed picture of Saville's work, the performers and plays he used, and the way he used them. It was still necessary to visit some libraries and archives for additional information, but I could never have put together such a rich collection of information without these digital resources.

My research has been put into a self-published book, filled with newspaper reviews of Saville's productions, and stories about his company. This is not just a narrow look at regional theatre; there are also some references to figures of national importance in theatre history. John Faucit Saville's sister, Helen Faucit, was a great star of her day, and his half-brother Henry Farren made his stage debut in Derbyshire with Saville's company. John Faucit Saville's wife Marianne performed with Macready on his farewell tour and also played at Windsor for Queen Victoria. The main interest for me, however, was the way theatre history reveals how national and local events impacted on society and public behaviour, and how the theatre connected with the life of the ordinary working man and woman.

Front cover of my self-published book about John Faucit Saville

If you are interested in playbills generally, you might want to help British Library provide more information about individual ones through a crowdsourcing project, entitled 'In the Spotlight'.

This blog post is by Dr Adi Keinan-Schoonbaert, Digital Curator for Asian and African Collections, British Library. She's on Twitter as @BL_AdiKS.

In the last couple of years we’ve teamed up with PRImA Research Lab in Salford to run competitions for automating the transcription of Arabic manuscripts (RASM2018 and RASM2019), in an ongoing effort to identify good solutions for Arabic Handwritten Text Recognition (HTR).

I’ve been curious to test our Arabic materials with Transkribus – one of the leading tools for automating the recognition of historical documents. We’ve already tried it out on items from the Library’s India Office collection as well as early Bengali printed books, and we were pleased with the results. Several months ago the British Library joined the READ-COOP – the cooperative taking up the development of Transkribus – as a founding member.

As with other HTR tools, Transkribus’ HTR+ engine cannot start automatic transcription straight away, but first needs to be trained on a specific type of script and handwriting. This is achieved by creating a training dataset – a transcription of the text on each page, as accurate as possible, and a segmentation of the page into text areas and line, demarcating the exact location of the text. Training sets are therefore comprised of a set of images and an equivalent set of XML files, containing the location and transcription of the text.

A screenshot from Transkribus, showing the segmentation and transcription of a page from Add MS 7474.

This process can be done in Transkribus, but in this case I already had a training set created using PRImA’s software Aletheia. I used the dataset created for the competitions mentioned above: 120 transcribed and ground-truthed pages from eight manuscripts digitised and made available through QDL. This dataset is now freely accessible through the British Library’s Research Repository.

Transkribus recommends creating a training set of at least 75 pages (between 5,000 and 15,000 words), however I was interested to find out a few things. First, the methods submitted for the RASM2019 competition worked on a training set of 20 pages, with an evaluation set of 100 pages. Therefore, I wanted to see how Transkribus’ HTR+ engine dealt with the same scenario. It should be noted that the RASM2019 methods were evaluated using PRImA’s evaluation methods, and this is not the case with Transkribus evaluation method – therefore, the results shown here are not accurately comparable, but give some idea on how Transkribus performed on the same training set.

I created four different models to see how Transkribus’ recognition algorithms deal with a growing training set. The models were created as follows:

• Training model of 20 pages, and evaluation set of 100 pages
• Training model of 50 pages, and evaluation set of 70 pages
• Training model of 75 pages, and evaluation set of 45 pages
• Training model of 100 pages, and evaluation set of 20 pages

The graphs below show each of the four iterations, from top to bottom:

The results can be summed up in a table:

Indeed the accuracy improved with each iteration of training – the more training data the neural networks in Transkribus’ HTR+ engine have, the better the results. With a training set of a 100 pages, Transkribus managed to automatically transcribe the rest of the 20 pages with 86.43% accuracy rate – which is pretty good for historical handwritten Arabic script.

As a next step, we could consider (1) adding more ground-truthed pages from our manuscripts to increase the size of the training set, and by that improve HTR accuracy; (2) adding other open ground truth datasets of handwritten Arabic to the existing training set, and checking whether this improves HTR accuracy; and (3) running a few manuscripts from QDL through Transkribus to see how its HTR+ engine transcribes them. If accuracy is satisfactory, we could see how to scale this up and make those transcriptions openly available and easily accessible.

In the meantime, I’m looking forward to participating at the OpenITI AOCP workshop entitled “OCR and Digital Text Production: Learning from the Past, Fostering Collaboration and Coordination for the Future,” taking place at the University of Maryland next week, and catching up with colleagues on all things Arabic OCR/HTR!