Digital Humanities @ Oxford Summer School

Dr Andrew Cusworth (University of Oxford)

What happens when archives become digital? How are digital archives made? Who does it? Where do they do it? And why?

In the course of addressing some of these questions, this strand will help its participants to frame and negotiate some of the major considerations in making and working with digital and digitalised archives. Through practical sessions and theoretical discussions, participants will gain insight into the possibilities and challenges presented by digital archives and working with cultural heritage materials digitally.

Working with both digitised and born digital materials, participants will be introduced to a number of core concepts and digital tools for collecting, cleaning and processing data for and from digital archives, as well as open-source solutions that can be used for cataloging, enriching, and publishing digital and digitised materials

Hands-on sessions will be complemented by lecture and seminar-style discussions of issues surrounding digital archival practice. These will help participants to frame the creation and use of digital archives within their theoretical, political, ethical, cultural, and technical contexts, and enable them to make more informed decisions in their future interactions with digital archives. 

View the full programme here.

Learning Objectives: 

• To better understand the technical underpinnings of digital archives and how these affect our interaction with our cultural heritage in a digital environment.
• To gain an understanding of how to prepare, work with, and publish a range of datatypes in a digital archive.
• To gain confidence in considering and discussing the critical, political, and ethical issues surrounding digital archives.

Level: Beginner

There are no specific skills requirements for this strand, and it is designed to suitable for anyone working with archives and their digital counterparts.

Dr Terhi Nurmikko-Fuller (Australian National University)

This workshop is an introduction to the theories and practices of capturing, querying, and publishing information online using the Linked Data method. Participants will learn about the theory behind Linked Data, and discuss challenges, opportunities, and the ethical considerations in using this methodology. During the workshop, participants will complete the workflow for converting tabular data into RDF (the Linked Data format).

View the full programme here. 

Learning Objectives:

• You will have an understanding of the terminology and jargon associated with Linked Data.    
• You will know at least one method for converting tabular data into RDF.    
• You will be able identify ways of applying Linked Data tools and methods to your research.    

Level: Beginner

Each participant must bring a laptop (not a tablet!) with the required software pre-installed. Please check that you have administrative rights to install software on your machine.

Dr Kevin Page (Oxford e-Research Centre) and Dr David Lewis (Oxford e-Research Centre)

A wealth of music and music-related information is now available digitally, offering tantalising possibilities for digital musicologies. These resources include large collections of audio and scores, bibliographic and biographic data, and performance ephemera--not to mention the ‘hidden’ existence of these within other digital content. With such large and wide ranging opportunities come new challenges in methods, principally in adapting technological solutions to assist musicologists when identifying, studying, and disseminating scholarly insights from amongst this tangle of forms, formats, and tools.
The Digital Musicology strand provides an introduction to computational and informatics methods that can be, and have been, successfully applied to musicology. Many of these techniques have their foundations in computer science, library and information science, mathematics and most recently Music Information Retrieval (MIR); sessions are presented from the perspective of interdisciplinary collaborations with musicologists by leading researchers in the field.

View the full programme here.

Learning objectives

• Recognise and distinguish digital formats used for different music sources, including audio data, symbolic data, and metadata
• Understand and appreciate the strengths and limitations of digital music formats and music processing methods, including how this might enable or constrain avenues of musicological scholarship
• Gain broad familiarity and practical experience to be able to select appropriate digital musicology approaches applicable to your own field of research; and sufficient insight, context, and confidence to seek out greater detail as an independent researcher

Level: beginner, but with familiarity with music/musicology

Workshop attendees should have some background or familiarity with music or musicology. No familiarity with digital methods is assumed. A basic grasp of music notation and theory is beneficial when putting digital methods from the course in context. Some familiarity with programming may be beneficial, but not essential: the strand includes a small number of sessions which include some programming, which take the form of guided notebooks. Attendees must bring their own laptop running MacOS, Windows, or Linux; tablets (e.g. iPadOS) are not sufficient. Attendees must have administrator access to their laptop and be comfortable installing and configuring new software--the strand relies on several specialised softwares which attendees will need to install and run on their own machines.    

Yasmin Faghihi, Huw Jones (University of Cambridge), Matthew Holford (Bodleian Libraries)

This workshop combines taught and practical sessions with case-studies introducing the use of the Guidelines of the Text Encoding Initiative (TEI), with a focus on the representation and publishing of primary sources. TEI is a very broad and flexible standard, so we will also concentrate on how TEI can best be used in specific research contexts.  We will showcase a number of projects in the fields of digital editing, text-analysis and publication. Case studies will cover both specific textual phenomena and those common to diverse media and genres. Core aspects of TEI to be covered in the hands-on exercise sessions include structural elements of texts, metadata, representing people, places, dates and groups, the transcription and description of documents, encoding correspondence, and how to query, transform and publish your texts.

No previous experience with markup, XML, TEI, or editing is assumed. Participants will leave with a grounding based on practical experience in what the TEI can do to represent both the physical and the linguistic features of documents, how it can inform the analysis of texts, and how it can form part of a publication pathway.

View the full programme here. 

Learning Objectives: 

• Understand key aspects of XML and related technologies (including XPath, schemas); be confident in creating, editing and navigating XML documents; be familiar with different pathways to publication.
• Understand TEI as a community, a consortium and a set of guidelines; be familiar in detail with the core modules of the TEI guidelines; understand the implementation of TEI in a number of real-world projects.
• Be ready to use TEI in your own research projects.

Level: Beginner

Dr Lia Costiner (University of Oxford)

This strand introduces methods for recording, analysing and displaying cultural heritage (sites, material and visual culture). This includes the digital capture of objects, the creation of 3D models, and the employment of these models in interactive immersive experiences.

View the full programme here. 

Learning Objectives:

• Participants will gain a broad understanding of a range of techniques used in recording, analysing and displaying cultural heritage. 
• Participants will learn the basics of 3D capture and 3D modelling, using photogrammetry and SketchUp.
• Participants will gain a basic understanding of how to create immersive experiences in virtual reality, using the software Unity.

Level: Beginner

No pre-requisite knowledge. Software will have to be downloaded prior to the course.

Meriel Patrick, John Southall, David Tomkins, Rowan Wilson (University of Oxford)

This strand introduces a variety of approaches to dealing with humanities data. It covers modelling, structuring, and working with data, plus longer-term curation and preservation. Data types discussed include textual, tabular, image-based and time-based media. Attendees will hear from presenters experienced in working with these methods, and be given the opportunity to try some of them for themselves via practical exercises. The goal is to equip researchers to select solutions that will work for them. 

View the full programme here. 

Learning Objectives:

• Learn about a range of methods for working with humanities data
• Gain an overview of key issues that need to be considered during data-driven humanities research
• Be encouraged to think about the continued value of their data after the end of their project, and to explore some of the options for preservation and sharing

Level: Beginner

Each participant is recommended to bring a laptop (not a tablet!). Please check that you have administrative rights to install software on your machine.

Dr Mariona Coll Ardanuy, Dr Kaspar Beelen and Dr Federico Nanni (Alan Turing Institute)

This hands-on workshop offers an introduction to natural language processing in Python, from processing texts to extracting meaning from them, as well as the basics of automated semantic analysis with machine learning. We will focus on practical applications (from preprocessing texts to enriching them with linguistic knowledge via part-of-speech tagging or syntactic parsing) and we will show how to work with raw, semi-structured, and tabular data. We will show the basics of topic modelling, and how this technique can be used for humanities research in order to explore the content of large collections. Finally, we will provide an overview of semantic analysis using word embeddings, and how this technique can be used for a large variety of humanities research, such as tracking semantic change or understanding biases in a corpus. At the end of the workshop, participants will have acquired basic practical skills and knowledge on how Python can be used for processing humanities textual data. They will leave with an understanding of key aspects of natural language processing and how these can be applied to their research in the humanities.

View the full programme here. 

Learning Objectives:

• Participants will leave with an understanding of key aspects of natural language processing and how these can be applied to their research in the humanities.
• Participants will acquire basic practical skills and knowledge on how Python can be used for processing humanities textual data.

Level: Beginner/Intermediate

No prior knowledge of Python or natural language processing is required. However, participants may find this workshop difficult to follow if they are not acquainted with the basic concepts of text analysis in digital humanities.

Dr Matteo Romanello (EPFL) and Dr Giovanni Colavizza (University of Amsterdam)

This workshop offers an introduction to data analysis techniques of practical use to humanities scholars and GLAM professionals. Topics include: data formats (XML, JSON), the Python data analysis stack (Pandas), how to get from messy to tidy data, basics of data analysis and visualization, advanced topics (modelling) and applications (topic modelling), best practices to communicate and share your results (licensing, repositories). Classes are hands-on and interactive, as we will work with real-world examples of metadata (e.g., the British Library catalog), text (e.g., historical newspapers) and relational data (e.g., social networks). Attendees will have the opportunity to work on their own projects and/or on proposed exercises. 

View the full programme here. 

Learning Objectives

• Learn how to use the main Python libraries for data wrangling and analysis to perform a variety of practical tasks.
• Apply the main data analysis tools and techniques in dealing with cultural data.
• Critically understand the surplus-value and limitations of data analysis from a humanities perspective.

Level: Advanced

This is an advanced workshop: exposure to Python and the basics of scripting is strongly recommended. This could be acquired for example via previous attendance of the Text2Tech workshop or equivalent courses or self-learning. A good refresher is Chapter 1 of http://www.karsdorp.io/python-course

Neil Jefferies (Bodleian Libraries, Oxford) and Dr Megan Gooch (Bodleian Libraries, Oxford)

This strand will showcase a range of methods and approaches to texts in the Digital Humanities. It will focus on introducing and explaining these techniques and providing examples of projects and research that use them. Topics covered will include a variety of TEI applications, various approaches to text analytics, automated transcription and an exploration of the different forms of textual information available form study. The aim is to help you understand the breadth of the field and identify technqiues relevant to your research interests that you can explore further.

View the full programme here. 

Learning Objectives

• Understand the breadth of text formats and techniques in the Humanties 
• Critically evaluate which formats, tools and techniques might be appropriate to your research requirements
• Have exposure to research projects which demonstrate these tools in action

 Level: Beginner

No coding or previous DH experience necessary