Cambridge Digital Humanities course timetable

Find out how to use blogging in your research. The first of two sessions on research blogging will explore the benefits and limitations of blogging for public engagement.

This workshop will examine strategies for transforming a variety of sources, from crumbling manuscripts to printed documents and books into digital data covering manual keying, OCR, and cutting-edge handwritten text recognition engines.

The second of two sessions on research blogging will explore how social media can enable public engagement with your blog, learn how to set up a Twitter chat and explore other methods to get people talking about your research.

Image big data are increasingly being used to understand the built and natural environment and to observe behaviours within it. Data sources include satellite and airborne imagery, 360 street views, and fixed video or time lapse traffic and CCTV cameras. While some of these sources are newer than others what has been changing are the quality of the images, the geographical coverage, and the potential for assessing changes over time. At the same time improvements in machine learning have made it possible to turn images into quantitative data at scale.

In this workshop we will explore the challenges that researchers face when using images at scale to understand environments and behaviours, building on work at Cambridge to estimate cycling levels, using satellite data to estimate motor vehicle volume, and planned data collection in Kenya using 360 cameras.

Learn to think visually and communicate using sound and film: participants will be introduced to the language of film, shot types, camera movements, framing, basic rules of camera use, how to tell a story, and editing in the Phoenix Training Suite.

Learn to think visually and communicate using sound and film: participants will be introduced to the language of film, shot types, camera movements, framing, basic rules of camera use, how to tell a story, and editing in the Phoenix Training Suite.

This workshop will discuss prospective methods and approaches for critically engaging with the images of people created through Generative Adversarial Networks, using design experiments as provocations to expand debate about notions of ‘realism’ and ‘authenticity’ in an era where human and machine vision are ever more systematically intertwined.

Find out how to shape a digital research project from scratch. This session will introduce the building blocks of online research design, from the several methodologies available to conduct the research to the ethical guidelines that should underpin our projects.

This session is a primer on digital data collection. The goal is to become familiar with online data sources and practices of internet-mediated data collection, including retrieving data from social media platforms.

Garbage in, garbage out! Your output is as good or as bad as your input. Data collected from online sources is often dirty and messy. Discover how to clean and organise your data. After transforming raw data into a structured dataset, you will be ready to perform data analysis.

This session introduces a variety of analytical strategies, with a focus on Social Network Analysis, the most widely used and abused method for analysing and visualising digital and social media data. At the end of this session, you will be familiar with the basic concepts, techniques and measures of social network analysis.

The shelf-life of your dataset dictates the longevity of your findings. Sharing your data and assuring its integrity is a fundamental part of a digital research project. In this session we will discuss the principles of open data, channels for data dissemination and the fundamentals of data preservation.

This workshop will examine strategies for transforming a variety of sources into structured digital data, ranging from crumbling manuscripts to printed documents and books.

This session will introduce basic methods for reading and processing text files in Python. We will walk through an example that reads in a large text corpus, splits it into tokens (words) and sentences, removes unwanted words (stopwords), counts the words (frequency analysis), and visualises results. We will talk about the 5 steps of text mining and what resources to use when learning text mining for your research in your own time. No prior knowledge of Python is required, and no installations will be needed. We will use web services available in your browser to follow along.

This session will introduce topic modelling. Topic modelling is looking for clusters of words that summarise the meaning of documents. We will talk about how to choose what sort of text mining you might want for your research. Some knowledge of Python is required, as gained from 'Introduction to Text-Mining with Python 1', or equivalent. No installations will be needed; we will use web services available in your browser to follow along with the examples.

Dr Nathan Crilly and Chih-Chun Chen explore the challenges of communicating complex ideas to diverse audiences through a variety of digital media formats. Three case studies will be reported from an EPSRC-funded research project which sought to clarify and communicate the nature of complex system design and its relationship to emerging technologies. For example, the project studied the way in which technologists working in Synthetic Biology and Swarm Robotics conceptualise and address the complexity of the systems they are designing. Outputs from the project include: • A 35-page ‘primer’ on the subject of complexity (now with over 6000 downloads) • A three-minute animated movie discussing the subjectivity of complexity (now with 2500 views) • An interactive website (implemented by Dr Chen since she has programming skills) that generates annotated bibliographies for complexity resources tailored to a user’s interests (launched in March 2019) Dr Crilly and Dr Chih-Chun will discuss the process of engaging with media partners, including working with science communication agencies, animators and film-makers, reflect on what they learned from the process and what they would do differently in future.

This workshop will examine database creation from historical documents. Extracting data from these can be hard work and involves quite unusual skill combinations. You may need to digitise and transcribe from primary sources, and then design and build a database from scratch with the information. Other sources you use could already be digitised but may be arranged or filed in an unsuitable way for your project and therefore need conversion. We will look at techniques used when employing crumbling manuscripts, printed documents, books, or text searchable images, to harvest historical data. Techniques include manual data-entry, scanning and OCR, and handwritten text recognition systems.

This session focusses on providing photography skills for those undertaking archival research. Dr Oliver Dunn has experience spanning a decade filming documents for major academic research projects. He will go over practical approaches to finding and ordering materials in the archive, methods of handling and filming them, digital file storage, and transcription strategies. The focus is very much on low-tech approaches and small budgets. We’ll consider best uses of smartphones, digital cameras and tripods. The session is held at the Digital Content Unit at the University Library.

Learn to think visually and to communicate using sound and film. Participants will be introduced to the language of film, shot types, camera movements, framing, basic rules of camera use, how to tell a story, and editing. Some prior knowledge of filming is required. Please see the CDH website for more details (www.cdh.cam.ac.uk).

Learn to think visually and to communicate using sound and film. Participants will be introduced to the language of film, shot types, camera movements, framing, basic rules of camera use, how to tell a story, and editing. Some prior knowledge of filming is required. Please see the CDH website for more details (www.cdh.cam.ac.uk).