All Cambridge Digital Humanities courses

The aim of this course is to support students, researchers, and professionals interested in exploring the changing nature of the English vocabulary in historical texts at scale, and to reflect critically on the limitations of these computational analyses. We will focus on computational methods for representing word meaning and word meaning change from large-scale historical text corpora. The corpus used will consist of Darwin’s letters from the (Darwin Project https://www.darwinproject.ac.uk/) at Cambridge University Library. All code will be in online Python notebooks.

If you are interested in attending this course, please fill in the application form

Methods Workshop: Best Practices in Coding for Digital Humanities

Mary Chester-Kadwell (CDH Methods Fellow)

Please note this workshop has limited spaces and an application process in place. Application forms should be completed by Tuesday, 11 May 2021. Successful applicants will be notified by end-of-day Wednesday, 12 May 2021.

This course introduces best practices and techniques to help you better manage your code and data, and develop your project into a usable, sustainable, and reproducible workflow for research.

Developing your coding practice is an ongoing process throughout your career. This intermediate course is aimed at students and staff who use coding in research, or plan on starting such a project soon. We present an introduction to a range of best practices and techniques to help you better manage your code and data, and develop your project into a usable, sustainable, and reproducible workflow. All the examples and exercises will be in Python.

If you are interested in attending this course, please fill in the application form. Places will be prioritised for students and staff in the schools of Arts & Humanities, Humanities & Social Sciences, libraries and museums. If you study or work in a STEM department and use humanities or social sciences approaches you are also welcome to apply.

If you are interested in attending this course, please fill in the application form.

Methods Workshop: Best Practices in Coding for Digital Humanities

Mary Chester-Kadwell (CDH Research Software Engineering Coordinator)

Please note this workshop has limited spaces and an application process in place. Application forms should be completed by noon Wednesday, 4 May 2022 (you can only access this form by signing into your University Google Account). Successful applicants will be notified by end-of-day Monday, 9 May 2021.

This course introduces best practices and techniques to help you better manage your code and data, and develop your project into a usable, sustainable, and reproducible workflow for research.

Developing your coding practice is an ongoing process throughout your career. This intermediate course is aimed at students and staff who use coding in research, or plan on starting such a project soon. We present an introduction to a range of best practices and techniques to help you better manage your code and data, and develop your project into a usable, sustainable, and reproducible workflow. All the examples and exercises will be in Python.

If you are interested in attending this course, please complete the application form.

Jessica M. Parr, PhD (Simmons University and The Programming Historian)

We welcome Jessica Parr as a guest lecturer for this Methods Workshop, where we will discuss mapping techniques for scholars of the transatlantic slave trade. It will open with a discussion of addressing the Eurocentricity of geospatial techniques and the archives. We will then discuss strategies for reading against the archive to locate Black voices and strategies for determining geospatial coordinates from primary sources. Finally, the workshop will conclude with a demonstration of how to create maps in Tableau and some discussion of data ethics.

Please apply for a place if you would like to attend, on registration, you will be asked to complete and submit an information form (which will remain open until 10 am Monday, 14 February 2022), places are limited and selected on a rolling basis, we would suggest early completion.  We will confirm participation week commencing Monday, 21 February 2022.

Text-mining is extracting information from unstructured text, such as books, newspapers, and manuscript transcriptions. This foundational course is aimed at students and staff new to text-mining. It presents a basic introduction to text-mining principles and methods, with coding examples and exercises in Python. To discuss the process, we will walk through a simple example of collecting, cleaning and analysing a text.

If you are interested in attending this course, please request a place and complete the application form, submitting it by the end of Monday, 7 March 2022. Successful applicants will be notified by the end-of-day Thursday, 10 March 2022. Preparatory materials will be released on Thursday, 17 March 2022. Places will be prioritised for students and staff in the schools of Arts & Humanities, Humanities & Social Sciences, libraries and museums. However, if you study or work in a STEM department and use humanities or social sciences approaches, you are also welcome to apply.

Text-mining is extracting information from unstructured text, such as books, newspapers, and manuscript transcriptions. This foundational course is aimed at students and staff who are new to text-mining, and presents a basic introduction to text-mining principles and methods, with coding examples and exercises in Python. To discuss the process, we will walk through a simple example of collecting, cleaning and analysing a text.

If you are interested in attending this course, please fill in, and return, the application form by Monday, 22 February 2021. Places will be prioritised for students and staff in the schools of Arts & Humanities, Humanities & Social Sciences, libraries and museums. If you study or work in a STEM department and use humanities or social sciences approaches you are also welcome to apply.

We are pleased to welcome Dr Ann Borda as a guest lecturer for this CDH Methods Workshop. Ann is the Participatory Health Lead in the Co-design Living Lab for Digital Health in the Centre for Digital Transformation of Health at the University of Melbourne. She is a Fellow of the Australasian Institute of Digital Health, Honorary Senior Research Associate at University College London, and sits on the policy committee of the Climate and Health Alliance. Ann formerly held collaborative positions in JISC and at the Science Museum London. Her research spans living lab and citizen science methods, and emerging participatory practices in digital health and culture.

There is an increasing presence in research incorporating participatory approaches to the production of knowledge. Participatory research is a range of methods framed within ideological perspectives. Its fundamental principles are that the subjects of the research become involved as partners in the process of the enquiry, and enacted through a set of social values. Participation can be classified by various degrees of involvement. Participatory activities can be expressed through various methods and approaches, such as co-design, citizen science, crowdsourcing, living labs, participatory action research and community-based participatory research, among others.

The TEI (Text Encoding Initiative https://tei-c.org/) is a standard for the transcription and description of text bearing objects, and is very widely used in the digital humanities – from digital editions and manuscript catalogues to text mining and linguistic analysis. This course will take you through the basics of the TEI – what it is and what it can be used for – with a particular focus on uses in research, paths to publication (both web and print) and the use of TEI documents as a dataset for analysis. There will be a chance to create some TEI yourself as well as looking at existing projects and examples. The course will take place over two sessions a week apart – with an introductory taught session, then a chance to work on TEI records yourself, followed by a review and discussion session.

Code in research helps to automate the collection, analysis or visualisation of data. Although the code may fulfil your research objective, you might have wondered how to improve it, code more efficiently, or make it ready for collaboration and sharing. Perhaps you have experienced challenges with debugging or understanding it.

In this intermediate workshop, we will introduce several coding design principles and practices that ensure code is reliable, reusable and understandable, enabling participants to take their code to the next level.

The workshop will begin by introducing the key concepts using ample examples. Participants will then work in groups to apply the concepts either to code provided by the convenor or to their existing projects, with guidance from the convenor. Participants will also have the opportunity to discuss their project goals with the convenor to demonstrate how the best practices can be implemented during the coding process.

This workshop is for individuals who have some prior experience with Python and who, ideally, have a coding project that they wish to work on. Participants are encouraged to arrive with a specific objective or desired output for their coding project. For example, you might wish to pre-process your data, add a specific analysis to your project, or make your code publicly available.

This workshop is a very basic introduction to network analysis for humanities scholars. It will introduce the concepts of networks, nodes, edges, directed and weighted networks, bi- and multi-partite networks. It will give an overview of the kinds of things that can be thought about through a network framework, as well as some things that can’t. And it will introduce key theories, including weak ties, and small worlds. There will be an activity where participants will build their own test data set that they can then visualise. In the second half of the workshop we will cover some networks metrics including various centrality measures, clustering coefficient, community detection algorithms. It will include an activity introducing one basic web-based tool that allows you to run some of these algorithms and will provide suggestions for routes forward with other tools and coding libraries that allows quantitative analysis.

Attendees should bring their own laptops.

Ruth Ahnert is Professor of Literary History & Digital Humanities at Queen Mary University of London, and is currently leading two large AHRC-funded projects: Living with Machines, and Networking Archives. She is author of The Rise of Prison Literature in the Sixteenth Century (2013), and co-author of Tudor Networks of Power, and The Network Turn (both forthcoming).