Digital Humanities @ Oxford Summer School

Join us in 2024, in Oxford and online, to engage with experts in the Digital Humanities on a wide range of topics alongside students and researchers at every stage of their career path.

The event will take place in Oxford, from 12-16 August. New for 2024: we will also have two digital strands, one on AI and Creative technologies and another in partnership with Research Libraries UK.

Registration

Registration will open in March 2024.

Prices

  • Full Commercial Early bird Rate - £850
  • Academic/Education/Not for Profit early bird rate: (you work for an educational institution, library, charity or not-for-profit organisation in any capacity) - £750
  • Students (you are enrolled as a full-time or part-time student at any educational institution at any level) - £650

Online attendance for one strand - £80.00

Payment is by debit / credit card only. Please do not email requesting an invoice or bank transfer.

We are also offering bursaries for the 2024 Summer School - applications close Friday 23 February 2024, full details can be found on this online form

Programme

Our full 2024 Summer School programme will be available soon. Our selection of keynote lectures from leading Digital Humanists will be announced shortly. Take a look at  some previous programmes:

Format

The 2024 Summer School will take place in St Anne's College, Oxford again and we look forward to welcoming you there.

Participants will be asked to choose one of the onsite or live-streamed strands. Full details can be found in our programme (coming soon).

William Nixon (Research Libraries UK) and Dr Andrew Cusworth (University of Oxford)

This is a new strand for 2024. This strand provides a range of primers across the breadth of Digital Scholarship activities which Research libraries support, deliver and lead on. Attendees will be introduced to tools, technologies and projects including text mining, image manipulation and transcription. It will also explore the potential of AI and its impact on Digital Scholarship.

  • Learn about a range of Digital Scholarship tools and technologies - Text Encoding Initiative (TEI), Text and Data Mining (TDM) and International Image Interoperability Framework (IIIF).
  • Gain insight into how various technologies and techniques could be used to support and enable Digital Scholarship. 
  • Develop confidence in identifying and selecting the appropriate tools to enable Digital Scholarship. 

Level: Entry-level.

This strand is offered in collaboration with Research Libraries UK.

In blue letters: RLUK Research Libraries UK
 
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 2023 programme here and the 2022 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
Meriel Patrick, John Southall, David Tomkins, Rowan Wilson (University of Oxford)

This strand introduces a variety of approaches to dealing with humanities data. Data types discussed include textual, tabular and visual. 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 those undertaking or supporting research with the knowledge to select from a range of solutions that will work for their projects.

View the 2023 programme here and the 2022 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: Introductory - no knowledge of specific software or techniques is assumed. 

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 2023 programme here and the 2022 programme here.

Learning Objectives:
  • Gain practical experience in processing textual data using Python.
  • Learn essential techniques for extracting meaning from texts, including part-of-speech tagging and named entity recognition.
  • Acquire proficiency in working with various types of data, such as raw, semi-structured, and tabular data.
Level: Beginner

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.

Sven Najem-Meyer and Paul Guhennec (EPFL)

This workshop offers an introduction to data analysis techniques of practical use to humanities scholars and GLAM professionals. Topics include: data formats (JSON, GeoPackage), 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 (geo mapping, network analysis), 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 chance to work on their own projects and/or on suggested exercises, and doing so is strongly encouraged.

View the 2023 programme here and the 2022 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: familiarity with the main concepts of Python programming is required (e.g. main data types (`list`, `dict`, `str`...), `for` loops, `if/else` statements, using and writing functions). This could be acquired for example via previous attendance of the Text2Tech workshop or equivalent courses or self-learning.

We have prepared a "Python requirements check" notebook, available in two formats: 1) as a static notebook (GitHub link) and 2) as a runnable notebook (MyBinder link). If you are at ease with the topics it covers, you meet the programming requirements for this workshop.

A good refresher of Python basics is Chapter 1 of http://www.karsdorp.io/python-course.

This strand is offered in collaboration with EPFL, the Swiss Federal Institute of Technology in Lausanne.

The letters E P F L in a bright red
Professor David De Roure (Oxford eResearch Centre and Digital Scholarship @ Oxford, Oxford) and Dr Jack Orchard (Bodleian Libraries, Oxford)

This strand offers an introduction to the principles and methodologies behind the use of creative and innovative technologies in digital humanities research, specifically Artificial Intelligence (AI), Augmented and Virtual Realities (AR & VR), Digital Games and Gamification. Attendees will be introduced to a range of theoretical and methodological approaches for working in these spaces, as well as being given an insight into the way current research projects are using these tools. Topics covered include Digital Ethnography & Autoethnography, Ethics and AI, Generative AI in research, Virtual Reality and Digital Heritage, Game Design as Research, and AI-Generated Music.

  • Understanding the History and Theory of AI.
  • Application of the principles and methodologies of AI and Creative Tech in their research.
  • Analysis of the current landscape of research projects in the field.
Level: Beginner.