Workshops and Lectures
WorkshopsPermalink
You will find below a first list of workshops, with the program and the instructors. More workshops will be presented in the following weeks, not only in English. Most of the workshops are planned to last the two weeks of the ESU (this year from 21 July to 2 August), some workshops will last one week (the dates will be specified in the workshop description).
AI and Image Analysis (Lauren Tilton, University of Richmond, USA)Permalink
The workshop will last one week, from July 28 to August 1 (week 2). What is an image? How do computers view images? How can we use AI to analyze images? The workshop will address these three questions through a combination of theory, methods, and practical skills. We will focus on
- understanding image files such as digitized manuscripts and artworks,
- organizing image data in connection with metadata such as author and provenance data, and
- analyzing features in images using AI such as objects and people.
We will build from more basic concepts such as color to more complex methods including multimodal large language models (MLLMs). A primary aim of this course is for participants to better understand what is possible through computational image analysis and how the approaches can further their interests. The course is designed for participants who are new or familiar with image analysis. No programming skills are required.
Digital Archives: Reading and Manipulating Large-Scale Catalogues, Curating and Creating Small-Scale Archives (Yael Netzer, Hebrew University, Israel)Permalink
The purpose of this two-week workshop is to develop practical and critical skills toward the representation of knowledge in digital archives and to build a small-scale digital archive. This workshop blends theory and hands-on activities, enabling participants to engage with digital catalogues, metadata structures, and archival curation tools.
Additional Open Lab Session: An optional free exploration day will be available for participants to receive one-on-one guidance on their projects and tools.
No prior knowledge is required for this workshop. Participants are encouraged to bring their own datasets but will be provided with starter collections if needed.
First Week – Reading and Working with Data / Collections in OpenRefine
Digital data in various formats is at the heart of humanities research. Often, datasets are large, messy, or structured in unfamiliar ways. This week, students will learn to inspect, clean, and enrich digital catalogues using OpenRefine, as well as how to enhance datasets with Linked Open Data (LOD) from sources such as the Library of Congress, VIAF, and Wikidata. By the end of this week, students will be proficient in:
- Understanding different file formats (CSV, TSV, Spreadsheets, JSON, XML TEI)
- Using regular expressions for data manipulation (with some skill and aid from chatGPT)
- Writing expressions with GREL (OpenRefine’s scripting language)
- Fetching and reconciling data via REST API (e.g., GeoNames, Wikidata)
- Scraping and structuring data from the web
- Mapping textual data to geographic locations
Schedule:
- Class 1: Introduction, loading a file, faceting, and exploring data
- Class 2: Regular expressions and working with dates
- Class 3: Clustering techniques for data cleaning
- Class 4: Fetching external data using REST APIs (GeoNames example)
- Hands-On Session: Practicing administrative tasks (changing working directory, memory allocation)
- Class 5: Reconciliation and enriching data with Wikidata
- Class 6: Handling JSON and XML file formats
- Class 7: Web scraping techniques and automation
- Class 8: From text to map – Geospatial representations in OpenRefine
- Class 9: Summary and discussion
Second Week – Building a Digital Archive: Archives of the Present
This week focuses on the creation and structuring of small-scale digital archives, but also introduces the concept of archives of the present—a critical reflection on how contemporary events, data, and digital traces shape our archival practices. Participants will work with their own or provided collections, conceptualizing metadata structures and curatorial strategies. The workshop covers best practices in digital archive development, including metadata schema selection, linked data integration, and user-friendly design.
The discussion of archives of the present will explore:
- How digital documentation of real-time events (social media, news articles, live-streamed content) can be archived
- The ethical challenges of archiving contemporary materials
- Methods for ensuring accessibility and preservation of ephemeral data
- The evolving nature of authority files and metadata in fast-changing digital environments By the end of this week, students will be proficient in:
- Theoretical foundations of archival studies
- Metadata structuring and best practices
- Using Omeka-S for archive implementation
- Using Tropy for organizing and annotating images
- Linking archives to external sources and ontologies
- Designing and publishing an accessible, structured digital archive
- Engaging with contemporary data collection and preservation strategies
Schedule:
- Class 1: Theory of archives – an introduction
- Class 2: Digital archives – examples and reviewing participant collections
- Class 3: Modeling the domain
- Class 4: Metadata – methods of description, challenges, and dilemmas
- Class 5: Introduction to Omeka-S – setting up and structuring an archive
- Class 6: Using Tropy – basic features and integration with Omeka
- Hands-On Session: Working on participant collections
- Class 7: Archives of the present – Capturing and preserving digital traces
- Class 8: Linking and integrating with external resources and authority files
- Class 9: Publishing – designing Omeka pages for public access
- Class 10: Summary and reflections
To enrich the learning experience, this workshop will aim to incorporate:
- Case studies of successful digital archive projects
- Collaborative group work, where teams handle different types of archival materials
- Expanded toolset beyond OpenRefine and Omeka, including basic Python for data manipulation and SPARQL for querying LOD sources
- Introduction to IIIF (International Image Interoperability Framework) for handling digital images in archives
- Machine learning-assisted metadata extraction, including OCR (Transkribus), Google Vision API, and Named Entity Recognition (NER)
- Sustainability and long-term digital archive maintenance strategies
Digital Curation and Cultural Heritage (Carol Chiodo, The Claremont Colleges, USA)Permalink
The workshop will last one week, from July 22 to July 26 (week 1). More description to come soon.
Digital XML-TEI Content Creation and Processing Aided by AI Tools (Alex Bia, University of Elche, Spain)Permalink
DESCRIPTION: In this workshop, you’re going to learn how to create documents using XML-based encoding schemes like TEI, HTML, and ePub. Additionally, you will discover how to manage document structure to normalize large collections and how to render and transform documents automatically using technologies such as CSS, XPath, and XSLT. We will also explore how the most recent AI tools can help us perform some of these tasks.
This workshop comprises two parts:
- Week 1: Introduction to XML-based technologies for text encoding deals with producing digital text documents using XML vocabularies like TEI and HTML, as well as related technologies (ePub, Markdown, etc.). This is a hands-on, introductory-level course. We will also introduce AI tools like ChatGPT to be used as an aid in document processing.
- Week 2: XML-TEI document structuring and rendering deals with designing and validating document structures, as well as producing polished renderings through CSS stylesheets and XSLT transformations. This is a hands-on, medium-high level course.
BRIEF BIO: https://alexbia.umh.es/bio-eng/brief-cv/
Distant Reading in R. Analyse the text & visualize the data (Artjoms Šeļa, Czech Academy of Sciences and Giovanni Pietro Vitali, University of Versailles Saint-Quentin-en-Yvelines)Permalink
Distant reading is one of the most well-known methodological approaches in digital humanities, formalized by Franco Moretti in the article Conjectures on World Literature (2000). It benefits greatly from computational tools. For this reason, we are proposing a course based on the use of R, one of the most popular programming languages in the scientific community today. The philosophy of the course is to analyze text and visualize data, and its structure follows this dichotomy. The objective is to introduce participants to different methodological perspectives and provide practical tools they can use in their own research. The course offers a compact introduction to natural language processing, computational text analysis, machine learning, graph theory, and geospatial humanities. By the end of the two-week course, participants will be able to use R and RStudio to apply textual and spatial analysis. An important component of the course is data visualization,, an area in which R excels, offering a comprehensive framework for creating graphs, maps, and trees. The final part of the course will focus on open-source programs like Gephi, GIMP, and Inkscape, which allow users to manipulate and rework vector and graphical files. The course is suitable for beginners who want to start their digital humanities training with a complete overview of the most common tools used for distant reading.
Humanities Data and Mapping Environments (David Wrisley, New York University, Abu Dhabi, UAE and Voica Pușcașiu, Babeș-Bolyai University, Romania)Permalink
This spatial humanities workshop will introduce participants to different ways of thinking about humanities data, their curation within projects, and their use in digital mapping environments. The workshop will not be a traditional course in Geographic Information Systems (GIS), although we will use open source GIS and web mapping along the way. The workshop is designed for the total beginner who would like
- to explore how a spatial dimension can enrich humanities and interdisciplinary research projects and
- to learn some fundamental skills for collecting and organizing data in order to be able to integrate such methods into their research workflows.
Drawing inspiration from the location of the ESU in the historical center of Besançon, participants will gather data from within the city and will work with data from local cultural institutions. The workshop will also introduce students to ways in which artificial intelligence and machine learning are opening up new horizons for spatial humanities research. The workshop lasts a total of 36 hours, two weeks of 18 contact hours each.
The central goals of the workshop are fourfold:
- to learn where we might obtain spatial data relevant to our research interests, or capture data from analog sources through digitization,
- to explore modeling data for a research project having a spatial dimension,
- to practice different ways that we can tell a story by visualizing spatial data, and
- to learn ways that we can disseminate and share that data.
In the first part of the course we conduct a critical review of a range of spatial humanities projects: their scope and the rhetorical strategies they employ for spatial storytelling and argument. We will begin by reflecting on how location-based research might be incorporated into research projects in different disciplines (cinema, art history, anthropology, history, literature, etc.) as well as the challenges of incorporating a spatial dimension into research. We will learn about the creation of data in formats relevant to spatial humanities projects (using gazetteers, mobile data collection, off-the-shelf software) as well as some basic querying in order to perform repetitive tasks for building a spatial dataset. Students will be introduced to normalization and wrangling techniques and will contrast the manual, slow creation of data with more automated forms of analysis.
In the second part of the course, we will learn some skills in static site development so that we can host our own basic web maps. We will experiment with other automated workflows and will turn to more complex forms of visualization and storytelling. Open-source GIS software will be used to learn about georeferencing / warping and the creation of historical vector / polygon data from digitized historical maps. Depending on the time available and participant interest, we may explore other topics of interest: discipline-specific gazetteers, mapping packages in R, OpenStreetMap, Wikidata, maps & IIIF, machine classification of features in historical or series maps, etc.
A Zotero library of supplementary readings will be provided by the instructors.
Text analysis/prompt engineering on historical data (Isuri Anuradha, Lancaster University/CLARIN)Permalink
This workshop is sponsored by CLARIN and will last for one week. More information to come soon.
Edition “géographique” numérique (Digital Text Edition and Mapping, Rudy Chaulet, University Marie and Louis Pasteur)Permalink
This workshop, in French, will last for one week (week 2). More description to come soon.
LecturesPermalink
The ESU also represents the opportunity to listen to conferences on various topics of Digital Humanities. The list and the schedules will soon be published.