Cambridge Digital Humanities course timetable

This in-person workshop will provide an accessible, non-technical introduction to Machine Learning systems, aimed primarily at graduate students and researchers in the humanities, arts and social sciences. No prior knowledge of programming is required.

We will focus on the technical, ethical and societal implications of embedding Machine Learning systems for classifying and generating texts and images into the world of work, with a particular emphasis on the impact of Large Language Models such as ChatGPT. We will explore these text generation systems in the context of longer histories of AI, including the ‘deep learning revolution’ in image-based Machine Learning systems which laid the foundations for popular text-to-image generation models such as StableDiffusion.

Participants will have the chance to both learn more about how AI works and also discuss what the embedding of such systems into labour processes, management structures, resource allocation systems may mean for how society works.

This session introduces the command line, sometimes also known as the shell or the terminal, to humanities researchers. No prior knowledge of the command line or programming of any kind is required or expected from attendees.

A basic understanding of how to use the command line provides a step change in how productive you can be when working with data or text files, particularly large number of files or very large files, which can be hard to manipulate in a graphical interface. Some tools and programs can only be used from the command line, and this session aims to give you the confidence to work with them. In the session we primarily look at seven George Eliot novels and a comparative set of seven Dickens novels (about 3.4 million words in total) but this session should be of use to any humanities researchers working with text collections and the principles have far broader applicability.

We'll focus on running programs which come pre-installed on Mac and Linux, and which can be easily added to Windows. We'll combine these programs in productive ways, discuss how to discover and use the options for each, how to send results to files, and how to work efficiently on the command line so you don't have to retype or remember everything you've done.

Following the introductory Methods Workshops, held on 21st November 2023, this session will focus on how to adopt the principles to the projects chosen by the participants. This will cover learning a practical approach to taking images fit for purpose in any conditions with available resources. It may also address any more advanced imaging topics such as image stitching, Optical Character Recognition, Multispectral Imaging, or photogrammetry if these are in the interest of the participants. It will also be an opportunity to visit the Digital Content Unit at Cambridge University Library.

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.

Across two sessions, participants will be introduced to the ancient yet evolving practices of commonplace-book keeping and the ‘modernised’ digital tools and methods for extracting, indexing, sustaining and networking knowledge fragments from personal notes, anthologies and archives for idea generation. Commonplacing—manifest as the classical vade mecums (‘come with me’ book of phrases for rhetors), the early-modern scholar’s indexed bodies of learnings, the eighteenth-century domestic commonplace books of culinary and medicinal recipes and nineteenth-century collaborative records of readings—is as much a method for knowledge compilation as a way to structure collective (and ‘re-collected’) thoughts. The commonplace book’s modern afterlife may be traced in the Zettelkasten method and micro-blogging sites like Tumblr, which facilitate the systematic storage and dispersal of quotations and other media.

The interactive sessions will draw upon the theoretical underpinning of commonplacing as a productive ideation approach as well as new digital tools of translating atomised ‘commonplaces’ (and metadata) into network graphs and databases for visualising potentially hidden connections for research and pedagogy.

Across two sessions, participants will be introduced to the ancient yet evolving practices of commonplace-book keeping and the ‘modernised’ digital tools and methods for extracting, indexing, sustaining and networking knowledge fragments from personal notes, anthologies and archives for idea generation. Commonplacing—manifest as the classical vade mecums (‘come with me’ book of phrases for rhetors), the early-modern scholar’s indexed bodies of learnings, the eighteenth-century domestic commonplace books of culinary and medicinal recipes and nineteenth-century collaborative records of readings—is as much a method for knowledge compilation as a way to structure collective (and ‘re-collected’) thoughts. The commonplace book’s modern afterlife may be traced in the Zettelkasten method and micro-blogging sites like Tumblr, which facilitate the systematic storage and dispersal of quotations and other media.

The interactive sessions will draw upon the theoretical underpinning of commonplacing as a productive ideation approach as well as new digital tools of translating atomised ‘commonplaces’ (and metadata) into network graphs and databases for visualising potentially hidden connections for research and pedagogy.

Please note this workshop has limited spaces and we request a pre course questionnaire is completed.

This Methods Workshop welcomes participants who are interested in acquiring skills related to Open Data Kit (ODK), a tool that facilitates the implementation of low-cost digital recording for field surveys. ODK is an open-source data collection platform, that can be used on mobile devices, offering a wide range of features for the development of customised digital survey forms. It allows users to collect geotagged photos, sketches, location coordinates, load pre-existing data, implement skipping logics, write questionnaires in multiple languages and more.

These forms are made using XLSForm standards which offers an easy to understand and simple way of authoring forms using Excel. ODK users can also collect data offline and send it to server when a good internet connection is available, allowing data to still be collected in areas of low internet connectivity. The collected data is submitted to the server from where it can be downloaded for analysis or further processing. In this workshop, you will be able to learn end-to-end ODK form development, deployment, setting up on a mobile device and analysing collected data. With these skills, you will then be able to design your own personalised field data collection system as per your research/project requirements.

Note: ODK Collect (mobile application) is currently only available for android devices. However, the forms can also be accessed using Enketo web forms in a browser on a laptop or on a mobile device e.g., iOS. Enketo web forms and ODK Collect are expected to have different appearance for survey forms as these are developed and maintained by different teams.

Convenor: Dr Estara Arrant (Cambridge University Library)

This session is aimed at researchers with minimal coding experience or who have not done any coding but have data they want to explore and visualise. However, you do not need to have a full set of data to benefit from this class. You will learn the fundamentals of conducting a basic analysis of Humanities-related data in the R language, including prepping and tidying data and generating useful graphs which communicate information about your research to others.  You will also gain a basic overview of the R programming language, which will provide you with principles that you can take forward to learn more advanced data analysis methods. The software we will use (RStudio) is free to download and is compatible with most computers. We will provide installation support and guidance. You will need your own laptop.

Please note this workshop has limited spaces, and an pre-course questionnaire is in place. Please complete before the session.

Version control helps you to write code for your research more sustainably and collaboratively, in line with best practices for open research. You might use code for collecting, analysing or visualising your data or something else. Everyone who codes in some way can benefit from learning about version control for their daily workflow.

This workshop will cover the importance of version control when developing code and foster a culture of best practices in FAIR (Findable, Accessible, Interoperable, Reproducible) code development. We will take you through the basic use of GitHub to help you store, manage, and track changes to your code and develop code collaboratively with others.

Designed with beginners in mind, this workshop caters to those who have not yet delved into Git or GitHub. While prior knowledge of a programming language (e.g., R or Python) would be beneficial, it is not a prerequisite.

Join our Methods Fellow, Amira Moeding in a workshop which introduces methods of historical enquiry into the development of digital technologies and digital data. How can we do the history of technology today? What are the limits of historical enquiry; what are its strengths? Moreover, what can we learn from historical narratives about technologies? More concretely, what can the history of “Big Data” tell us about artificial intelligence today? What were, for example, seen as the pitfalls and problems with biases early on in the development of data-driven applications?

Together with you, Amira will think through and employ methods of historical enquiry and critical theory to gain a better understanding of the origin of ‘data-driven’ digital technologies. Therein, the workshop attempts to bring about both an understanding of the statistical or data-driven methods by asking how they came about and why they became attractive to whom. The workshop thus links technologies back to the interests and contexts that rendered them viable. This line of enquiry will allow us to ask what ‘technological progress’ currently is, how stories of ‘progress’ are narrated by industry actors, and what ‘risks’ become apparent from their perspective. By providing this contextualisation and recovering early interests that drove developments in artificial intelligence research and ‘Big Tech’, we will also see that progress, and the promises for the future that it holds, are not ‘objective’ or ‘necessary’ but localised in time and space. We will raise the question to what degree digital humanities cannot only use digital methods to aid the humanities, but how historical and philosophical methods can be employed to provide a basis for criticising and theorising ‘the digital’ and putting the methods so-called ‘artificial intelligences’ are based on into perspective.

Convenor: Dr Giulia Grisot (Cambridge Digital Humanities)

This workshop will delve into the intricacies of sentiment analysis using R, offering participants a comprehensive understanding of this text mining technique and a chance to gain hands-on experience with sentiment scoring methodologies and advanced sentiment visualisation. Designed for intermediate R users, this session aims to equip attendees with the requisite skills to extract nuanced insights from textual data through the lens of R programming. You will need your own laptop.

It is often said we live in a society saturated with data. Visualisation methods can play a crucial role in helping to cut through the information overload. Badly designed charts, graphs and diagrams, on the other hand, can confuse or deceive. This session will introduce and contextualise graphical communication practices historically and culturally, helping you to think more critically about your own work and that of others.

We will focus on graphical display as an interpretative and persuasive practice which requires as much attention to detail as writing. A hands-on collaborative exercise using historical data will give you the chance to put your visualisation skills to work. Coding skills are not required for this workshop but a basic familiarity with creating graphs and charts will be helpful. If you need to refresh your skills before the session, please use this open access workbook: https://docs.google.com/document/d/1wtwqIsWVGcsQ6rvXAzdpfNL5f7mUqV5k_Rr7ZrQCnbo/edit. (if the link doesn't work from UTBS, please copy and paste into your browser).