CCDHHN

AVAnnotate Open Source Application for Audiovisual Digital Exhibits and Editions (DHSI 2026)
2026-06-15 00:00 - 2026-06-19 23:59 (America/Halifax) | Université de Montréal, 3150 Rue Jean Brillant, Montreal, Québec, H3T 1N7, Canada
Description

This course introduces participants to AVAnnotate, an open-source digital humanities tool for creating annotated audiovisual exhibits. Through hands-on exercises with sample media, participants will learn how to set up projects, create annotations for accessibility and research, and explore case studies in teaching and scholarship. By the end of the week, participants will have built and presented their own projects, gaining practical skills for integrating audiovisual materials into digital research and pedagogy.

Prerequisites: No technical prerequisites are required. Familiarity with basic digital tools and an interest in working with audiovisual collections will be helpful, but all levels of experience are welcome.

Instructor(s)

Jack DeVry Riordan is a PhD student in the Department of Spanish and Portuguese at the University of Texas at Austin. His research focuses on contemporary Cuban cinema, and the ways in which digital humanities tools can be used for the curation and sharing of audiovisual works. Since September 2025, he has been working with AVAnnotate, exploring how digital annotation and archival practices can expand access to and engagement with audiovisual materials. More broadly, his work bridges film studies and digital humanities, with an emphasis on fostering new methods of preserving and disseminating cultural memory.

Automatic Text Recognition of Historical Documents: Building Text Corpora and Datasets (DHSI 2026)
2026-06-15 00:00 - 2026-06-19 23:59
Description

The course will be an introduction to automatic text recognition technologies, focusing on the example of Kraken and eScriptorium but including an overview of other existing solutions. At the end of the course, participants will have a better understanding of machine learning through the example of automatic text recognition, will have first-hand experience using transcription software, producing data and models, as well as publishing and reusing special datasets for training transcription models. They will be able to understand how to organize a transcription campaign individually or as a team while complying with existing standards for annotation. The course is intended for participants with little to or no knowledge about automatic transcription. Students, librarians, and all scholars are welcome.

Instructor(s)

Alix Chagué is a specialist in automatic text recognition applied to historical documents. Her PhD thesis, which she will defend in 2026, especially focuses on questions relating to Open Science and data creation for using and training transcription models. She has contributed to the development of several essential infrastructures for the advancement of automatic transcription, among which the open source application Scriptorium and the ecosystem for the publication of reusable gold data for text recognition HTR-United. Since 2019, she has taught several workshops introducing automatic text recognition and its software solutions to beginners or advanced users.

Agile Project Management for Humanities Research (DHSI 2026)
2026-06-15 00:00 - 2026-06-19 23:59
Description

Agile project management is about negotiating the completion of a project from beginning to end while remaining flexible. Being patient and delaying decisions until you have to make them, gathering as much information as you can in the meantime, and then taking action with the information you have, always keeping alternatives in mind in case your first plan of action doesn’t pan out. It’s about more than just negotiating within the rules. It’s about changing the rules of the game to better ensure a successful project.

Over the course of the week, participants will learn about how different teams could approach managing different aspects of a project. Participants will explore applying these to their own project(s). By the end of the week, participants will have an initial plan of action for managing their own project(s).

Instructor(s)

Over the years, James Smith has had computing interests that include exploring REST, linked open data, and other components of the web-as-platform as a foundation for building sharable, long-lived digital contributions to the humanities. More recently, he has focused on emphasizing the human element in computing.

Click here for an example of previous syllabus and course material (2025)

Introduction to Multimodal Time Series Analysis with Python for Humanists (DHSI 2026)
2026-06-15 00:00 - 2026-06-19 23:59
Description

Data sets with rich underlying temporal dynamics are ubiquitous across the Humanities. A non-exhaustive list includes oral history interviews, medieval chronicles, news streams, diaries, as well as biographies. Even songs, poems, and novels can be approached as temporal data. Time series analysis is a branch of modern data science aiming to investigate temporal dynamics; it is an analytical and exploratory framework to study events and their relationship to time. It also offers groundbreaking solutions to explore temporal data that is unfolding through various modalities. For instance, an oral history interview is unfolding through different modalities or layers such as the textual content by the speaker, and the speaker’s body posture and eye movement. The overall goal of this course is to provide a practical introduction to single- and multimodal time series analysis tailored for humanists who have basic programming skills in Python. Specifically, our course has three goals.

First, it aims to teach the basic operations in time series analysis such as slicing, time stamping, and aggregation. As part of this, the course will guide participants through the process of transforming Humanities data sets into time series. We will discuss how existing essentially non-temporal data sets (such as a poem) can be treated as time series. We will also show how LLMs can help in the process of annotating time series and producing multimodal time series.

Second, our course will prepare participants to analyse the resulting time series. Participants will get acquainted with key concepts of time series analysis such as waiting time, recurrence, and frequency, and their connections to multimodality.

Finally, we will also teach some rudimentary statistical frameworks (survival analysis, time-to-event analysis, trend and seasonal analysis) to extract meaningful information from single- and multimodal time series.

Participants will be encouraged to bring their own data and work with that throughout the course, which will be structured as follows. In the mornings, we will offer more theory oriented sessions. By contrast, the afternoons will be devoted to practice and programming. We will provide reusable code in the format of Jupyter notebooks.

As a whole, after our course, students will be able to explore and analyse single- and multimodal temporal dynamics in a rich array of Humanities data sets, and raise meaningful questions related to the underlying temporal dynamics.

This course is for a broad Humanist audience who already has experience with Python and does data intensive research.

Instructor(s)

Gabor Mihaly Toth is a research scientist at the Center for Contemporary and Digital History at the University of Luxembourg; he is the principal investigator of “Voices from Auschwitz: Unlocking the Collective Memory with the Multimodal Analysis of Survivor Testimonies” project; before joining the University of Luxembourg, he had worked at the University of Southern California and Yale University.

Mohamed Laib is Data Science researcher in the Trustworthy AI group at the Luxembourg Institute of Science and Technology, with a solid foundation in statistics and machine learning. His work focuses on leveraging these skills to tackle complex real-world challenges.

[Foundations] Outils numériques et études littéraires: vers de nouvelles perspectives critiques (DHSI 2026)
2026-06-15 00:00 - 2026-06-19 23:59
Description

Ce cours propose un aperçu des méthodes numériques appliquées aux études littéraires. Il s’adresse aux débutant·e·s intéressé·e·s par le potentiel du numérique dans leurs recherches et souhaitant découvrir une diversité de techniques. Nous explorerons des exemples novateurs de recherches en études littéraires, en abordant les méthodes et la gestion des données qui les rendent possibles. Une approche critique guidera l’introduction de plusieurs méthodes, telles que l’analyse automatisée des textes, la stylométrie, la cartographie numérique et l’analyse computationnelle d’images. À l’issue de ce parcours, divisé entre ateliers pratiques et discussions théoriques, les participant·e·s auront une meilleure compréhension des méthodes computationnelles appliquées à une variété de perspectives critiques. Il sera possible ensuite d’approfondir leur expertise de manière autonome ou en participant à d’autres formations spécialisées du DHSI.

Ce cours sera enseigné en français, avec des lectures et des exemples tirés de différentes langues, y compris l’anglais.

Enseignant.e.s

David Joseph Wrisley est professeur titulaire en humanités numériques à la New York University Abu Dhabi (Émirats arabes unis). Il a obtenu son doctorat à Princeton en langues et littératures romanes, avec une spécialisation en littérature médiévale comparée. Il s’intéresse à l’application des méthodes computationnelles en sciences humaines, particulièrement dans les contextes multilingues et non-anglophones. Ses recherches actuelles portent sur le développement de modèles de reconnaissance d’écriture manuscrite (en latin, arabe et français médiéval) ainsi que sur d’autres usages de l’intelligence artificielle dans l’étude des sources historiques. Depuis plus de 20 ans, il est engagé dans l’interdisciplinarité et la collaboration dans les pays du monde arabe. Avant de s’installer à Abou Dhabi, il a enseigné à l’American University of Beirut (Liban) de 2002 à 2016. A présent il co-dirige le Paris Bible Project (parisbible.github.io) et le groupe de recherche OpenGulf (opengulf.github.io).

Parham Aledavood est candidat au doctorat en littérature, option humanités numériques, à l’Université de Montréal. Sa recherche doctorale est soutenue par une bourse du Fonds de recherche du Québec (FRQ). En associant la théorie postcoloniale, les études planétaires et les humanités numériques, sa recherche actuelle porte sur une analyse computationnelle du traumatisme et du genre dans les romans de migration contemporains. À partir de septembre 2024, il est le directeur adjoint du Digital Humanities Summer Institute (DHSI).

Cliquez ici pour accéder au matériel pédagogique du DHSI 2025
