News

Ceilidh and the Too Many Harlequins, Part 2

Editor’s note: Welcome to the second installment in our new series, the London Stage Data-Sitters Club! Not sure what that means? Check out our brief orientation to the series here, and read all posts to date under the category: London Stage Data-Sitters Club. Today’s post is the second of two by LSDB Research Assistant Ceilidh McCallum, and it picks up where “Ceilidh and the Too Many Harlequins” left off last week. – Mattie Burkert While my DH capstone project on Harlequin afterpieces focused on performances and plots, another question evolved alongside the research process: Who were the most popular Harlequin and Columbine involved with this set of afterpieces? At the same time that I was beginning my capstone research, I was working on a project for the LSDB, gathering biographies of notable people from A Biographical Dictionary of Actors, Actresses, Musicians, Dancers, Managers and Other Stage Personnel in London, 1660-1800, a... Read More

Ceilidh and the Too Many Harlequins

Editor’s note: Welcome to the first installment in our new series, the London Stage Data-Sitters Club! Not sure what that means? Check out our brief orientation to the series here, and read all posts to date under the category: London Stage Data-Sitters Club. Today’s post is the first of two by Ceilidh McCallum, whom you might already know as one of the LSDB’s Research Assistants and who (like all the Data-Sitters) just completed the capstone course for the University of Oregon’s undergraduate Minor in Digital Humanities. – Mattie Burkert The interactive data visualization below represents the theaters where The Beggar’s Opera was staged between 1728 and 1800, highlighting the Harlequin afterpiece that was most frequently performed alongside John Gay’s comedy at each playhouse. It ‘paints a picture’ of the cultural relevance of different plots and which were selected for each location. Visualization created by Ceilidh McCallum using Processing; translated into JavaScript using... Read More

Introducing the London Stage Data-Sitters!

I’m a huge fan of the Data-Sitters Club: a site full of fun, informative tutorials and reflections on digital humanities research methods, all centered on the classic YA lit series The Babysitters’ Club. Each “book” (blog post) pays homage to an installment in the original series: BSC #1 Kristy’s Great Idea becomes DSC #1 Quinn’s Great Idea, and so on. A rotating cast of core Data-Sitters and guest bloggers write about their experiences gathering, processing, analyzing, and interpreting a shared corpus — in this case, the BSC novels — offering workflows, resources, and problem-solving techniques that readers can learn from to tackle their own humanities text mining projects. Visit their website to learn more About the Data-Sitters’ Club Inspired by (and with permission from!) the Data-Sitters themselves, I’m delighted to announce a new series on this blog, which we’re calling the “London Stage Data-Sitters’ Club.” Over the coming weeks, we’ll be featuring guest posts from... Read More

Getting a Handle on the Data

Erin M. Winter is a Research Data Management Librarian at the University of Oregon, where she teaches and consults on data management, Python, version control, and SQL. She has been an informationist and technical jack-of-all-trades for the London Stage Database since 2025. Incremental Improvements Earlier this month, we released an update to the London Stage Database that corrects thousands of rows. While this release is comparatively small in scope, I wanted to use it as an opportunity to explain what database revisions mean for our users and how these subtle changes improve the usability and accuracy of the site. Albion and Albanius with its corrected title as displayed in the Related Works interface. Some of the most obvious corrections included fixing typos in work and performance titles. Our Works table once featured an Albion and Alabanius, but that’s now been corrected to Albion and Albanius, the proper title of the 1685 opera. As a... Read More

Data Science Takes the Stage

My name is Quynh-Tran Le, and I am a Research Intern on the London Stage Database team. As a Data Science major, I come with a background in data processing, which I am using to help improve LSDB’s compatibility with other datasets. In particular, I have been focused on aligning London Stage records with the formats used by the new Transnational Stages project to compare performance cultures in other global cities of the eighteenth century. Data scientists work through multiple data sets to identify patterns, trends, and relationships between features, often using statistical modeling and analysis. These methods can also support the goals of researchers in humanities fields. Literary scholars analyze dramatic texts to understand the themes and styles of specific works using its textual data, while historians also use performance records to analyze the economics and audience demographics of a theater. Their research methodology usually involves closely reading individual... Read More

The World of the Beggar’s Opera

For the past two months, students in my advanced English courses have been collaborating on an interactive timeline designed to immerse readers in the world of John Gay’s musical comedy, The Beggar’s Opera, which premiered in 1728 and provided the blueprint for every West End musical since. Students in my literature class–“Viral Media in Eighteenth-Century London”–read and studied the play, visited our Library’s Special Collections to view rare materials from the period, and conducted original research into the politics, crime, censorship, celebrity, and scandal that swirled around the play’s premiere. They handed off their research to students in “Technologies and Texts: Digital Humanities Capstone,” who designed and implemented a digital storytelling experience as multi-modal and multi-layered as Gay’s smash hit. Both groups drew on LSDB in their work, although their research stretches far beyond the database and, indeed, beyond the eighteenth century. The timeline is embedded below, but for a better... Read More