Cambridge Digital Humanities course timetable

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

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.

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.

In this CDH Basics session, we will discuss how to assess the impact of relevant legal frameworks, including data protection, intellectual property and media law, on your digital research project and consider what approach researchers should take to the terms of service of third-party digital platforms. We will explore the challenge of informed consent in a highly networked world and look at a range of strategies for dealing with this problem. 

This CDH Basics session is aimed at researchers who have never done any coding before. We will explore basic principles and approaches to writing and adapting code, using the popular programming language Python as a case study. Participants will also gain familiarity with using Jupyter Notebooks, an open-source web application that allows users to create and share documents containing live code alongside visualisations and narrative text.

This CDH Basics session investigates three different methods for accessing digital data ‘in bulk’: using an API (Application Programme Interface), web scraping and direct access (via download or on a hard drive). We will explore the importance of good practice in documenting the provenance of data that others have created and discuss the practical steps in research data management essential to ensuring that you are able to make legal and ethical use of this type of data in your research. No knowledge of programming languages is required, however, there will be a demonstration of a Python web scraper during the session and references to more in-depth tutorials on web scraping will be provided.

Data which other people have created is often either unstructured or structured in the wrong way for the questions that you want to answer. Rather than reinventing the wheel and collecting it all over again, this CDH Basics session introduces participants to OpenRefine, a free ‘power tool’ for dealing with messy data. In order to work with OpenRefine you will need administrator privileges to install software on your laptop. 

The impact of well-crafted data visualisations has been well-documented historically. Florence Nightingale famously used charts to make her case for hospital hygiene in the Crimean War, while Dr John Snow’s bar charts of cholera deaths in London helped convince the authorities of the water-borne nature of the disease. However, as information designer Alberto Cairo notes, charts can also lie. This introductory CDH Basics session presents the basic principles of data visualisation for researchers who are new to working with quantitative data.

This CDH Basics session introduces the IIIF image data framework, which has been developed by a consortium of the world’s leading research libraries and image repositories and demonstrates a range of different machine learning-based methods for exploring digital image collections.

Machine learning-driven systems for seeing and sorting still and moving images are increasingly common in many contexts. This CDH Basics session explores the technical fundamentals of machine vision and discusses the societal and cultural impact of these systems, including the challenges and opportunities faced by humanities and social science researchers using computer vision systems as research tools.

Ensuring long-term access to digital data is often a difficult task: both hardware and code decay much more rapidly than many other means of information storage. Digital data created in the 1980s is frequently unreadable, whereas books and manuscripts written in the 980s are still legible. This CDH Basics session explores good practice in data preservation and software sustainability and looks at what you need to do to ensure that the data you don’t want to keep is destroyed.