Digital Humanities @ Oxford Summer School

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 2024 programme here, 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

Neil Jefferies, Meriel Patrick, 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 2024 programme here, the 2023 programme here and the 2022 programme here

Learning Objectives:

• Learn about a range of methods for working with humanities data.
• Gain insight into how various technologies and techniques could be used to enhance a research project.
• Develop confidence in identifying and selecting the appropriate approach for a given project.

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.

We will focus on practical applications (from preprocessing texts to enriching them with linguistic knowledge via part-of-speech tagging or named entity recognition) and we will show how to work with text and tabular data. We will show the basics of language modeling, and how this technique can be used for humanities research for tasks such as tracking semantic change or understanding biases in a corpus, or in order to explore the content of large collections.

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 2024 programme here, 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 2024 programme here, 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 (e.g. exploration, reporting, visualization).
• 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.

Professor David De Roure (Oxford eResearch Centre and Digital Scholarship @ Oxford, Oxford) and Dr Jack Orchard (Bodleian Libraries, Oxford)

If you are new to digital humanities, this lecture-based survey strand gives you a thorough overview of the theory and practice of the subject. We draw on expertise from across the University of Oxford and our national and international collaborators, and on the University's library collections tow give you an insight into what digital humanities is, why it can be useful in research, and some examples of digital humanities in practice. This strand will appeal to anyone new to the field, or curious to broaden their understanding of the range of work the digital humanities encompassed.

The strand will be a mixture of lectures, discussions and some practical workshops so you will understand how your research or work can benefit from digital humanities theories, practices or policies."    
    

• You will be able to understand a range of digital humanities technologies, theories and practices and evaluate what is appropriate for your own work or study
• You will be familiar with the ways digital humanities has been applied in a range of subject areas and different roles
• You will be able to know where to look for further digital humanities resources to apply to your own work or study

Level: Beginner.