‘Visualising the medieval manor’: Extracting data to explore medieval women’s lives

Research Libraries UK and The National Archives offer a Professional Fellowship Scheme, allowing staff the time and resources to focus on a research project with the support of knowledgeable mentors across both organisations.

Fellows explore a professional practice question, develop new skills and knowledge, and share their learning with members of Research Libraries UK and The National Archives. This year we awarded two fellowships, which we’ll explore in a short series of blogs.

The first fellow to share their work is Karen Sayers. Since 2011, Karen has been an archivist at Leeds University Special Collections, with a wide-ranging remit including cataloguing, acquiring new material, and supporting internships. Her research interests are in medieval history and local studies.

Here Karen describes the work her fellowship has enabled, developing a Toolkit for Archivists and Librarians Supporting Research and Teaching in Digital Humanities.

– Lily Colgan, Academic Engagement Officer, The National Archives

The professional practice question I focused on for my Fellowship was the use of historical record series as data. I wanted to identify resources to enable archivists to support researchers and academic staff carrying out digital humanities projects using data from archives.

I decided that the best way to do this was to become a researcher and undertake a mini digital humanities project. I chose to extract data from the Wakefield Court Rolls from 1331–32 and use it to create visualisations to reveal aspects of medieval life to a wider audience. My project, ‘Visualising the Medieval Manor’, was born.

Top of a handwritten list on brown animal vellum, held down by weights. — Head of the Wakefield Manor Court Roll 1331. The first entry after the initial column is the case of Richard and Elizabeth Ricard who sued Edusa Preste for debt. YAS/MD225/1/57. Image credit: Leeds University Library

Data Sources

The Wakefield Court Rolls are a rich source of data about people’s lives on the Manor of Wakefield. From a time when the experiences of ordinary men and women were rarely recorded, the court records provide an insight into their daily lives. They contain data about the cases brought before the court, including people’s names, dates, fines, and types of action.

Middle of a handwritten list on brown animal vellum, including one entry with many separate, short lines. — Wakefield Manor Court Roll 1331. This faded sheet lists the case of Alice Walker, who was unsuccessfully sued by John Lorimer over the tenancy of a stall at Wakefield market. YAS/MD225/1/57. Image credit: Leeds University Library

My first step was to identify digital humanities projects that had analysed historical record series. Some have websites such as the Witches project and Enslaved: Peoples of the Historical Slave Trade, with visualisations and searchable databases. Projects like these gave me inspiration for what can be achieved with data.

The Wakefield manorial court rolls 1331–32 are a data-rich source. My first decision was what data to extract. I wanted to find out more about women’s lives and the types of offences or legal claims they were involved in, so I gathered data relating to cases which mentioned women.

Extracting Data

The rolls have been transcribed and uploaded to the Internet Archive, but the inconsistent punctuation, spelling of names and the way women are identified meant it was difficult to extract the data into structured columns in a spreadsheet. For example, women are often referred to as ‘wife of’ or ‘handmaid of’ rather than by their own name.

The ‘handmaid of John Harillul’ is one such unnamed woman. I decided to read the data, select relevant information, and input it into the spreadsheet. Processing the data was not going to be as straightforward as I had hoped!

Date	Person	Type of case	Position	Action	Fine in pence
18/10/1331	Cecily Hudelyn	debt	plaintiff	compromise
8/11/1331	Christine de Aula	debt	plaintiff	compromise
8/11/1331	Alice Leulyn	trespass	defendant	amercement against	6
8/11/1331	Agnes Peger	trespass	defendant	amercement against	2
8/11/1331	Emma Bilton	trespass	defendant	amercement against	24
8/11/1331	Alice wife of Robert	detinue (action to recover possessions)	defendant	unresolved
8/11/1331	handmaid of William Michel	theft of dry wood	defendant	amercement against	2
8/11/1331	daughter of John Nelot	theft of dry wood	defendant	amercement against	2
8/11/1331	Agnes Hogg junior	theft of dry wood	defendant	amercement against	2
8/11/1331	handmaid of Thomas Preest	theft of dry wood	defendant	amercement against	2

Sample data extracted from the Wakefield Court Rolls 1331–32, Court Baron. The action of detinue against Alice was to recover a fork. The dry wood was taken from the lord’s forest. An amercement was a monetary payment or fine.

Standardising Data

I standardised the data by removing or correcting wrongly formatted, duplicated or incomplete entries. In the medieval period the spelling of surnames varied. Importing the spreadsheet into OpenRefine to use its facet option was helpful as I could compare similar surnames, such as Agnes Bul and Agnes Bull. I was confident that these were the same person and combined the entries.

I learned from experience and other researchers that cleaning data often takes more time than gathering it. However, software packages can only interpret and visualise clean data. Cleaning also avoids spurious results from incomplete or incorrect information.

On reflection, I realised that I had developed many of the skills required for gathering and recording standardised data from historical record series through my archival cataloguing work. For example, I have recorded and cleaned metadata in spreadsheets and imported it into a collections management system to create catalogue records, which was useful experience.

Visualisation Software

I found mastering the terminology and some functions of data visualisation software packages the greatest challenge. I prefer in-person courses, but accessed online learning resources for PowerBI and Tableau Public because they were easily available. Some previous training on quantitative methods, although rusty, helped. I created basic graphs from data on women’s cases and found that the most effective visualisations are simple.

Bar chart showing 20 crimes against the number of cases, with 'debt' at the top with almost 80 cases, and 'defamation' at the bottom with just one. — Graph created in Excel showing different types of cases involving women in the Wakefield Court Baron, September 1331 – October 1332. Image credit: Leeds University Library

Conclusion

I found my fellowship rewarding. The greatest challenge was finding time to master the range of skills involved in a digital humanities research project, including extracting and cleaning data, and learning to create visualisations. I concluded that most projects are best undertaken by a collaborative project team combining their skills.

Archivists can be valuable contributors to, and partners in, digital humanities projects, sharing their metadata skills and collections knowledge. My Toolkit for Archivists and Librarians Supporting Research and Teaching in Digital Humanities is now available.