Cambridge Digital Humanities course timetable

This session provides a brief introduction to different methods for capturing bulk data from online sources or via agreement with data collection holders, including Application Programme Interfaces (APIs). We will address issues of data provenance, exceptions to copyright for text and data-mining, and discuss good practice in managing and working with data that others have created.

• Data collection methods

• Introduction to working with APIs

• Data brokerage

• Provenance and integrity

• Assessing intellectual property, copyright and Data Protection issues

• Documentation of collection methods

This Methods Workshop will introduce advanced techniques used for the digitisation and preservation of archival material. The first workshop will introduce the following topics:

• Copyrights and sensitive data considerations
• Understanding Photography basics
• Digitisation Imaging Standards
• Scene and capture calibration
• Image post-processing
• Taking usable images in any conditions
• Principles and Digital Preservation good practice

Completing the workshop will give participants a good understanding of archival photography best practices. You will gain a strong professional vocabulary to discuss imaging and a toolkit to assess image quality.

A second session, bookable separately, will focus on how to adopt those 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.

Convenor: Giulia Grisot (CDH Methods Fellow and a Visiting Academic)

This Methods Workshop will deliver an introduction to R Studio and R Markdown; the workshop will run through the functionalities and advantages of using R Studio and related tools for organising and analysing data, as well as for writing and referencing.

About the convenor: Giulia has a mixed background in Literary Linguistics, Psycholinguistics and Digital Humanities and has gained experience in both qualitative and quantitative approaches to texts and language in general, becoming familiar with several coding languages (R, python) essential for statistical as well as corpus investigations.

Giulia is currently working with large corpora of Swiss German fictional texts, looking at sentiments in relation to represented spatial locations, using both lexicon-based methods and machine learning.

Convenor: Tom Kissock (CDH Methods Fellow)

This Methods Workshop will offer Video Data Analysis for Social Science and Humanities students. It’s a relatively new, broad, and innovative multi-disciplinary methodology that helps students understand how video fits into modern research both inside and outside academia. For example, Cisco has estimated that video will make up 80% of internet traffic and 17.1% of it will be live video which is a 15-fold increase since 2017; therefore, it’s a tool that cannot be overlooked when conducting research.

Tom will address how to use video ethically, for example:

• Informed consent
• Storage
• Privacy

and also practically;

• Building timelines
• Coding schemes
• Presenting research findings

Tom will also plans to include a lesson focussed on viewing livestreams in a reflexive manner as this is a huge topic in the TikTok era

About the convenor: Tom has fifteen years’ experience as a Director, Executive Producer, and Livestream expert for the BBC, YouTube, NBC, and Cisco; coupled with seven years’ experience researching video witnessing and human rights abuses. In 2020 he received his MSc in Globalization and Latin American Development from UCL where his research used Video Data Analysis as a research methodology. He tracked how populist politicians in Brazil built misinformation campaigns by strategically cross-sharing videos to avoid journalistic questioning as a symbolic accountability mechanism during the 2018 presidential elections.

His PhD in Sociology at the University of Cambridge is a loose extension of his MSc, but explores positive aspects of streaming advocacy, such as how Indigenous video activists in Brazil use live video on platforms like Instagram, TikTok, and Kwai to reach audiences to discuss climate change, the environment, and land rights. He is interested in how video can produce knowledge and, subsequently how societies value different knowledge through the process of video witnessing. In his spare time, he serves as the Executive Producer of Declarations: Human Rights Podcast (part of Cambridge’s Centre for Governance and Human Rights), has given lectures on live streaming and human rights at MIT, UCL, and the University of Essex, and has written pieces for LatAM Dialogue and the Latin American Bureau.

Convenor: Tom Kissock (CDH Methods Fellow)

This Methods Workshop will offer Video Data Analysis for Social Science and Humanities students. It’s a relatively new, broad, and innovative multi-disciplinary methodology that helps students understand how video fits into modern research both inside and outside academia. For example, Cisco has estimated that video will make up 80% of internet traffic and 17.1% of it will be live video which is a 15-fold increase since 2017; therefore, it’s a tool that cannot be overlooked when conducting research.

Tom will address how to use video ethically, for example:

• Informed consent
• Storage
• Privacy

and also practically;

• Building timelines
• Coding schemes
• Presenting research findings

Tom will also plans to include a lesson focussed on viewing livestreams in a reflexive manner as this is a huge topic in the TikTok era

About the convenor: Tom has fifteen years’ experience as a Director, Executive Producer, and Livestream expert for the BBC, YouTube, NBC, and Cisco; coupled with seven years’ experience researching video witnessing and human rights abuses. In 2020 he received his MSc in Globalization and Latin American Development from UCL where his research used Video Data Analysis as a research methodology. He tracked how populist politicians in Brazil built misinformation campaigns by strategically cross-sharing videos to avoid journalistic questioning as a symbolic accountability mechanism during the 2018 presidential elections.

His PhD in Sociology at the University of Cambridge is a loose extension of his MSc, but explores positive aspects of streaming advocacy, such as how Indigenous video activists in Brazil use live video on platforms like Instagram, TikTok, and Kwai to reach audiences to discuss climate change, the environment, and land rights. He is interested in how video can produce knowledge and, subsequently how societies value different knowledge through the process of video witnessing. In his spare time, he serves as the Executive Producer of Declarations: Human Rights Podcast (part of Cambridge’s Centre for Governance and Human Rights), has given lectures on live streaming and human rights at MIT, UCL, and the University of Essex, and has written pieces for LatAM Dialogue and the Latin American Bureau.

Convenors: Leah Brainerd & Alex Gushurst-Moore (CDH Methods Fellow)

Centuries of ceramics. Millenia of maquettes. How do we grapple with large datasets? Join archaeologist Leah Brainerd and art historian Alex Gushurst-Moore to increase your computational literacy, learn how to scrape data from collections databases, and interpret that data through visual means.

Over two, two-hour sessions, you will be introduced to:

• Collections databases: what they are, how they are built, and how to navigate them
• Web-scraping: how do you go from a webpage on the internet to a dataset on your computer? A basic introduction to how web-scraping with R *Statistics works with a worked example, ethics of data, and learn how to evaluate a website for future data collection
• Data visualisation software: what options are available and how to use the open-source, online system mapping tool, Kumu
• Cultural evolutionary theory: cultural evolution is the change of culture over time; explore a theoretical perspective that views cultural information as an evolutionary process which teaches us, through cultural transmission, more about human decision making

The workshop will take place over two sessions. The first session (30 January) will cover collections databases and web-scraping. The second session (6 February) will cover data visualisation and cultural evolutionary theory. These sessions will consist of practical tutorials and discussion with the course leads. After each session, participants will be given an optional task to try out new skills acquired, on which they can receive feedback from the course organisers.

Convenors: Leah Brainerd & Alex Gushurst-Moore (CDH Methods Fellow)

Centuries of ceramics. Millenia of maquettes. How do we grapple with large datasets? Join archaeologist Leah Brainerd and art historian Alex Gushurst-Moore to increase your computational literacy, learn how to scrape data from collections databases, and interpret that data through visual means.

Over two, two-hour sessions, you will be introduced to:

• Collections databases: what they are, how they are built, and how to navigate them
• Web-scraping: how do you go from a webpage on the internet to a dataset on your computer? A basic introduction to how web-scraping with R *Statistics works with a worked example, ethics of data, and learn how to evaluate a website for future data collection
• Data visualisation software: what options are available and how to use the open-source, online system mapping tool, Kumu
• Cultural evolutionary theory: cultural evolution is the change of culture over time; explore a theoretical perspective that views cultural information as an evolutionary process which teaches us, through cultural transmission, more about human decision making

The workshop will take place over two sessions. The first session (30 January) will cover collections databases and web-scraping. The second session (6 February) will cover data visualisation and cultural evolutionary theory. These sessions will consist of practical tutorials and discussion with the course leads. After each session, participants will be given an optional task to try out new skills acquired, on which they can receive feedback from the course organisers.

Convenor: Dita N. Love (CDH Methods Fellow)

Sarah Ahmed and Jackie Stacey wrote that “speaking out about injustice, trauma, pain and grief have become crucial aspects of contemporary life which have transformed notions of what it means to be a subject, what it means to speak, and how we can understand the formation of communities and collectives” (p.2, 2001) in the introduction of the special issue Testimonial Cultures. These workshops ask therefore: what does it mean to centre survivor-knowledge, and witness together the aftermath of intersecting violence, when language and traditional methods often fail to re-present the experience of trauma? How can we avoid tokenising creative-digital research under the pressures of a precarious academy and creative sector?

Convenor: Dita N. Love (CDH Methods Fellow)

Sarah Ahmed and Jackie Stacey wrote that “speaking out about injustice, trauma, pain and grief have become crucial aspects of contemporary life which have transformed notions of what it means to be a subject, what it means to speak, and how we can understand the formation of communities and collectives” (p.2, 2001) in the introduction of the special issue Testimonial Cultures. These workshops ask therefore: what does it mean to centre survivor-knowledge, and witness together the aftermath of intersecting violence, when language and traditional methods often fail to re-present the experience of trauma? How can we avoid tokenising creative-digital research under the pressures of a precarious academy and creative sector?

This Methods Workshop will introduce advanced techniques used for the digitisation and preservation of archival material. The first workshop will introduce the following topics:

• Copyrights and sensitive data considerations
• Understanding Photography basics
• Digitisation Imaging Standards
• Scene and capture calibration
• Image post-processing
• Taking usable images in any conditions
• Principles and Digital Preservation good practice

Completing the workshop will give participants a good understanding of archival photography best practices. You will gain a strong professional vocabulary to discuss imaging and a toolkit to assess image quality.

A second session, bookable separately, will focus on how to adopt those 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.

Convenor: Orla Delaney (CDH Methods Fellow)

What does it mean to prioritise small data over big data?

Cultural heritage datasets, such as museum databases and digital archives, seem to resist the quantitative methods we usually associate with data science work, asking to be read and explored rather than aggregated and analysed. This workshop provides participants with a non-statistical toolkit that will enable them to approach, critique, and tell the story of a cultural heritage dataset.

Together we will consider approaches to the database from the history of science and technology, media archaeology, and digital ethnography. This will be done alongside an overview of practical considerations relevant to databasing in the sector, such as standards like FAIR (Findable, Accessible, Interoperable, Reusable) and CARE (Collective Benefit, Authority to Control, Responsibility, Ethics), specific technologies like linked data, and the results of recent projects aiming to criticise and diversify the underpinning technologies of cultural heritage databases. This workshop is aimed both at cultural heritage professionals and students, and at data science researchers interested in introducing a qualitative approach to their work.

This project begins from the premise that ‘transparency’ is not clear at all. Transparency is historically mediated, culturally constructed, and ideologically complex. Understood expansively, transparency is enmeshed with a variety of functions and associations, having been mobilised as a political call to action; a design methodology; a radical practice of digital disruption; an ideological tool of surveillance; a corporate strategy of diversion; an aesthetics of obfuscation; a cultural paradigm; a programming protocol; a celebration of Enlightenment rationality; a tactic for spatialising data; an antidote to computational black boxing; an ethical cliché; and more.

Across two workshops, we will explore the multidimensionality and intractability of transparency and investigate how the demand for more of it—in our algorithms, computational systems, and culture more broadly—can encode assumptions about the liberational capacity of restoring representation to the invisible. As a group we will conduct a survey of transparency and its political ramifications to digital culture by learning about its conceptual genealogies; interrogating its relevance to art and architecture; questioning its limits as an ethical imperative; and mapping it as a contemporary strategy of anti/mediation. Drawing on a combination of artworks, historical texts, cultural touchstones, and moving images, these workshops will give participants an opportunity to attend to transparency’s complex configurations within contemporary culture through a media theoretical lens. This project is designed to facilitate collaborative study; foster inter-disciplinary discourse; promote experimental learning; and develop a more theoretically nuanced and historically grounded starting point for critiquing transparency and its operations within digital culture.

Convenor: Estara Arrant (CDH Methods Fellow)

This methods workshop will teach students three powerful machine learning algorithms appropriate for Humanities research projects. These algorithms are designed to help you identify and explore meaningful patterns and correlations in your research material and are appropriate for descriptive, qualitative data sets of almost any size. These algorithms are applicable to virtually any Humanities field or research question.

• Multiple Correspondence Analysis: automatically identifies correlations and differences between specific data elements. This helps one to understand how different features (‘variables’ or ‘characteristics’) of one’s data are related to each other, and how strong their relationships are. This can be useful in almost any research project. For example, in a sociological dataset, this analysis could help clarify relationships between specific demographic characteristics (race, gender, political affiliation) and socioeconomic status (working class, education level, income bracket).
• K-modes clustering and hierarchical clustering: finding groups of similarity and relationship within the entirety of your data. Clustering helps one to identify which variables/characteristics group together, and which do not, and the degree of difference between groups. For example, such clustering could allow an art historian to see how paintings from one decade are characterised by style and artist, as contrasted to paintings from another decade (thus tracking shifts in artistic trends over time)

This workshop will specifically cover the following: Determining when your research could benefit from machine learning analysis. Designing a good methodology and running the analysis. Interpreting the results and determining if they are meaningful. Producing a useful visualisation (graphic) of the results. Communicating the findings to other scholars in the Humanities in an accessible way. Students will actively implement a small research project using a practice dataset and are encouraged to try out the methods in their current research. They will learn the basics of running the analysis in R’s powerful programming language.

Convenor: Mary Chester-Kadwell -  Lead Research Software Engineer, Cambridge Digital Humanities

Please note this workshop has limited spaces and an application process in place. Application forms should be completed by noon, Sunday, 12 March 2023. Successful applicants will be notified by the end-of-day Tuesday, 14 March 2023. 

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. Please ensure you are logged onto your University Google account to access the form further help here

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.

Key topics covered in the sessions will include:

• Situating Machine Learning in the longer history of Artificial Intelligence
• Machine Learning system architectures
• The challenges of dimension reduction, classification and generalisation
• Sources of bias and problems of interpretation
• Machine Learning applications and their societal consequences

During the session participants will be encouraged to work through practical exercises in image classification. No prior knowledge of programming is required. Participants wishing to run the experiments for themselves will need access to a laptop, but no special software is required, just an up-to-date web browser and an internet connection. We will be using Google Colab for the text generation experiments which you have access to via your Raven log-in. The image classification experiments will require a GitHub account ([sign up here https://github.com/])

Speaker: Mark Algee-Hewitt, Associate Professor of English and Director of the Stanford Literary Lab.

About this Methods workshop

At the heart of many of the current computational models of language usage, from generative A.I. to recommendation engines, are large language models that relate hundreds of thousands, or millions, of words to each other based on shared contexts. Mysterious products of complex modelling algorithms, these objects raise a number of practical (and ethical) questions for Humanities scholars: How are these language models created? What kinds of relationships does their math encode? How do biases in the corpus affect the model? And how can we effectively use them to answer humanities-based questions?

In this workshop, we will explore these questions using a medium-sized language embedding model trained on a corpus of novels. Using approachable code in the R software environment, participants will learn how to manipulate a model, assess similarities and difference within it, visualise relationships between words and even train their own embeddings.

This month we are calling on the expertise of students and staff here at Cambridge to bring underrepresented histories ‘out of the shadows’ and into the light on Wikipedia.

No prior Wiki experience is required! We will host an online training session at 11am on 17 May to get you started. This session will also be recorded and made available.

On 24 May we will host our edit-a-thon at the University Library. This drop-in event will allow you to access support throughout the day to help improve and expand Wikipedia’s content. Hosted jointly by Doing History in Public, Cambridge University Libraries, and Cambridge Digital Humanities, with the assistance of Wikimedia UK, we hope to get as many new pages created and edits made as possible. Refreshments will also be provided to fuel your efforts.

If you cannot be in Cambridge on 24 May, we will also do our best to enable you to interact remotely. You can also follow updates on Twitter via the hashtag #OOTSwiki.

This CDH Basics session explores the lifecycle of a digital research project across the stages of design, data capture, transformation, and analysis, presentation and preservation. It introduces tactics for embedding ethical research principles and practices at each stage of the research process.

• Introduction to the digital project life cycle

• Ethics by design and EDI-informed data processing

• Data and metadata - definitions

• Basics of data curation (good practice in file naming, version control)

• Understanding files and folders