Digital Humanities Summer Institute

For those new to the field, this is an introduction to the theory and practice of encoding electronic texts for the humanities. This workshop is designed for individuals who are contemplating embarking on a text-encoding project, or for those who would like to better understand the philosophy, theory, and practicalities of encoding in XML (Extensible Markup Language) using the Text Encoding Initiative (TEI) Guidelines. No prior experience with XML is assumed, but the course will move quickly through the basics. During the course we will provide online space for the practical application of project planning and technical knowledge acquired throughout the week.

This course is intended to be an introduction to the spatial humanities both in practice and theory and is suitable for both novices and those with more experience. The course will consist of readings, lectures, and hands-on practice with basic GIS and other softwares. An emphasis will be placed on spatial humanities as a way of thinking. By the end of the course, students will have a basic toolset to apply the techniques and theory of spatial humanities to both their research and teaching. This course will combine lecture, seminar, and hands-on activities with emphasis on the latter.

This course introduces current practices in encoding, analysing, and presenting music information. It will begin by introducing the philosophy, theory, and practicalities behind encoding symbolic music notation and will then explore pathways for analyzing and publishing that encoded data. Participants should have a basic knowledge of how to read music, but no prior experience with coding or XML is assumed.

This course for beginners will explore the how and why of podcasting. We’ll consider the benefits of the medium, and learn how to plan, record, edit, and publish audio content. Expect to do some listening and reading outside of class time, and have your favourite audio and text editors ready.

This course will cover the basics of project management from project definition to project review upon completion. Topics such as budget setting and controls, risk management, critical path scheduling, software tools, and related Internet resources will also be discussed. Material will be covered through lectures, discussions, case studies, and presentations. By the end of the course, participants will be able to implement the course concepts and tools in their projects.

This course has lecture, seminar, and hands-on components.

In this team-taught workshop, we invite scholars to join us in exploring the relationship between generative AI and the future of programming pedagogy in the digital humanities and a frontline of what the MLA-CCCC Joint Task Force on Writing and AI called “critical AI literacy.” Generative AI offers opportunities to make programming more accessible to diverse learners, and we explore how to use these emerging technologies to build inclusive pathways into programming through natural language interfaces and “literate programming.” This course will emphasize two critical programming languages, JavaScript and Python, that are commonly taught in humanities courses due to their applicability for interactive experiences, public humanities, and textual analysis. This workshop will build participants’ comfort with both generating and debugging code with AI tools, as well as deploying generative AI outside of mainstream commercial projects. Participants will be invited to approach GitHub, Copilot, Hugging Face, TensorFlow, and Jupyter Notebooks through a beginner’s mind, working through, critiquing, and developing assignments and pedagogical applications or their own classrooms. Participants with and without programming experience are welcome.

This course will guide attendees through the process of developing and enhancing student engagement and educational digital humanities programming using equity, advocacy, and care frameworks. Informed by liberatory and feminist pedagogies, this workshop will demonstrate how to build DH programming that meets the diverse educational and research needs of students, faculty, institutions, and community partners. Participants will read and discuss critical studies that explain how experiential and educational digital humanities programming can be used to build equitable and interdisciplinary learning spaces that enhance career readiness and skill-building for students while contributing to the research of faculty and community partners. Participants will actively ideate, collaborate, and construct strategies for designing advocacy-driven digital humanities labs, curriculum modules, and experiential programs that integrate with equity curriculum. They will write program goals, explore funding options, design recruitment plans, learn about project management techniques, find technical support options, and develop program assessments. By the end of the course, attendees leave with can project plan that they can implement at their institutions.

This workshop provides an introduction to the web of data for humanities researchers and cultural data stewards. Linked open data is highly structured interoperable data hosted on the web that is structured with semantic relationships so that machines can become partners in discovering, disseminating, sharing, and analyzing data. Done right, LOD contributes to a semantic web of resources that can be accessed and used across multiple online locations, aggregating knowledge and facilitating its reuse: it is FAIR (findable, accessible, interoperable, reusable) data in the most profound sense. The workshop will cover reasons for publishing cultural and research collections as LOD by looking at a range of existing uses in humanities research and GLAM (gallery, library, archive, and museum) contexts.

Participants will gain hands-on experience with several linked open data projects and tools; learn about the resource description framework (RDF), ontologies, and vocabularies used to create linked open data; learn how LOD can be leveraged in queries, visualizations, and web applications; gain an understanding of how LOD is created; and be introduced to a number of practical, ethical, and theoretical considerations that should inform the creation and reuse of diverse, nuanced, responsible, and usable linked open data for cultural research and dissemination. By the end of this workshop, participants should have grasped the major concepts of linked open data and the components of its technology stack; understand the basics of linked data creation, publication, and use; and be positioned to start to develop a linked data project of their own.

Intended audience: Advanced students, subject matter experts and researchers, librarians and data curators from GLAM contexts, research software engineers, and the LOD-curious!

This course will explore all aspects of conceptualizing, planning for, and creating a digital edition. It provides a basic introduction to the various types of digital editions, the practice of editing in the digital age, and a survey of the many digital tools available to serve project goals. Approaching a digital edition means taking time to think about how end-users will want to work with a particular edition. Beginning with the research and analytical needs of end-users in mind, editors are better able to develop effective editorial strategies that will result in a dynamic, useful, and usable digital edition. In this course, participants will engage in hands-on learning and group discussions related to project conceptualization, editorial policies and processes, and the selection and use of digital tools that can serve the needs of researchers and other end-users. Participants will bring a few sample materials they are working with. We will use these in a class project – creating a digital edition over the course of the week using skills learned in each session. Our goal is for participants to return to their home institutions ready and able to build upon, enhance, and transform these initial ideas into robust digital editions.

This offering is co-sponsored by the Center for Digital Editing (CDE).

Queerness and the digital humanities share a common ethos: a desire to make meaning in new ways. Indeed, the intersection of DH and queerness is a site of rich potential that can inspire (and challenge) us to think differently about DH, its methods, its purpose, and its politics. This is true whether we are building a DH project or writing DH critique.

This course draws from readings, discussions, interactive exercises, visits by guest speakers, and short, collaborative hands-on making projects to explore a variety of questions about queerness and DH. What does DH bring to queer studies? What does queer studies bring to DH? How might a queer DH project serve social justice? How can we develop DH projects that are queer in their design? What might it mean to queer DH itself? How can we understand DH as already queer? This course values self-reflection, intersectional perspectives, and cultural critique. It addresses the challenges and frictions facing those who do queer DH work. What are the obstacles for queer DH within larger structures of academia and funding? Is there a tension between the push for skill-building within DH and queer studies’ critiques of neoliberalism? When do the norms of DH themselves run counter to the values of queerness?

Our readings will address topics that fall under the wide umbrella of the “digital humanities,” including (but not limited to) data visualization, classification systems, programming languages, video games, mapping and geography, online archives, and tangible computing. As instructors, we bring to this course an understanding that LGBT/queer people, identities, and histories are multiple and complex. We strive to foster thinking about queerness and DH that engages meaningfully with intersecting issues of race, class, disability, nationality, religion, and indigenous rights.

This course introduces graduate students and faculty to the digital teaching and publishing tools available through COVE (Collaborative Organization for Virtual Education), a nonprofit, scholar-driven, open-access platform. Designed for ease of use, COVE enables instructors and scholars to create dynamic, interactive learning experiences without requiring technical expertise.

COVE operates as a two-part system: COVE Studio, which allows instructors to curate anthologies of primary texts for collaborative multimedia annotation, and COVE Editions, which supports the publication of scholarly and student-driven projects, including annotated editions, digital galleries, interactive maps, and timelines. COVE also facilitates peer review, making it an ideal venue for both scholarly publishing and student engagement.

Participants in this course will explore the pedagogical principles of “open assembly”—the free and transformative remixing of texts, archival materials, and digital resources to support active learning. Through hands-on engagement, they will construct an anthology in COVE Studio and initiate a project in COVE Editions (such as an edition, map, gallery, or timeline). By the course’s conclusion, participants will have developed materials that they can refine and implement in their own teaching or research and will share their work with the DHSI community.

This is a basic introduction to JavaScript, which is the programming language of the web. The class is designed for anyone interested in developing a website, or creating an interactive data visualization. By the end of this course, you will be able to read JavaScript you find online and adapt it to your needs. You will also have an opportunity to work with common JavaScript libraries/tools and enhance your own research practices.

This is a beginner to intermediate-level course in computational text analysis. It will focus on using digital tools to enhance and deepen traditional ways of reading and analyzing texts. We will explore ways of answering questions about authorship, textual, chronological, and authorial style, genre, and meaning, using some freely available and easy-to-use tools, such as ‘LIWC’ or ‘Stylo’ and most commonly applied methods, such as stylometry.
While stylometry, i.e. the analysis of countable linguistic features of texts has been usually associated with authorship attribution, the same methods are successfully applied to more general text analysis, and, recently, even analysis of other modes such as music, image and video. The statistics of even such simple features as word, word n-gram or character n-gram frequencies are not only a highly precise tool for identifying authorship but can also reveal patterns of similarity and difference between groups of works, as well as individual works, or specific voices within them, such as idiolects of characters in novels. Such methods are also frequently applied to compare works by one author or various authors or translators, and finally between works differing in terms of chronology, genre or narrative styles, etc. The results of computational text analysis can be compared and confronted with the findings of traditional studies, opening a new set of questions about style and its transfer, as well as the nature of particular features and language.
With this course, we aim to help participants build the knowledge and skills required to identify the problem they want to examine, define relevant research questions and apply the right method, and, finally, to design and complete their own experiments from corpus building to interpretation of results. Participants will learn how to use major modern stylometric methods in a reliable and reproducible manner, from simple keyword extraction and feature selection and analysis, to supervised and unsupervised machine learning based on text features, followed by visualization techniques ranging from PCA and dendrograms to networks. The software used in the course can easily be installed and run on participants’ own computers. While we do not expect the participants to have strong programming skills, having a basic understanding of running and reading code can improve the course experience and allow the participants to benefit more from the course. We will provide text corpora for training purposes but also encourage participants to bring their own data and research problems to work on during the course.

This course combines elements of courses previously taught at DHSI by Computational Stylistics Group (Maciej Eder, Jan Rybicki, Joanna Byszuk, Jeremi K. Ochab), i.e. ‘Stylometry with R’, DIY Computational Text Analysis with R’, as well as ‘Out of the Box Text Analysis’ taught by late David Hoover.

This class teaches you how to navigate and process XML using tools designed for the purpose–XSLT, XQuery, and Schematron. We cover these together as members of the same XML family, sharing a common syntax in XPath. New and experienced coders of XML will benefit alike from this course, whether just beginning a project or seeking to update and refresh skills. Our goals are 1) to share strategies for systematically building archives and databases, and 2) to increase participants’ confidence and fluency in extracting information coded in XML in those archives and databases. XPath is the center of the course, but we will show you how it applies in multiple XML processing contexts so that you learn how these work similarly and how these are used, respectively, to validate documents and to transform them for publication and other reuse. We’ll apply XPath to check for accuracy of text encoding–to write schema rules to manage your coding (or your project team’s coding).

You’ll practice and gain fluency in writing XPath expressions and patterns, including sequence expressions, regular expressions, datatypes, predicates, operators, and functions (from the core library and user-defined). We’ll write XPath to calculate how frequently you’ve marked a certain phenomenon, or locate which names of people are mentioned together in the same chapter, paragraph, sentence, stanza, or annotation. You’ll learn how XPath can help you to build exciting visualizations from XML code (such as to make a chart like a timeline or a network graph). Whether you are an XML beginner or a more experienced coder, you’ll find that strengthened skills in XPath and the XML family will help you with systematic encoding, document processing, and project management.

This is a hands-on course.

Have you ever looked at the wide variety of courses offered at DHSI and wondered what all those technical terms mean? Or had problems deciding on which technologies might be best suited for your work or most interesting to pursue further? This course is meant to provide a broad overview of technologies that are often used (and talked about) in the Digital Humanities. While it cannot (and is not meant to) serve as a replacement for any of the technology-focused workshops at DHSI, this course can provide a foundation to help you make informed decisions on where to direct further studies as well as get you over the initial hurdle. Each technology will be approached through a mixture of lectures and exercises.

Proposed topics: We will survey the following technologies and methods: How does a computer work?; Image and video editing; Audio recording and editing; XML and text encoding; Text analysis; 3D Modelling; Content Management Systems; and Geographic Information Systems. This course will have lecture, demo, and hands-on components. It is a good foundation for all tool- and technology-oriented DHSI offerings.

This course is intended for humanities-based researchers with no programming background whatsoever who would like to understand how programs work behind the scenes by writing some simple but useful programs of their own. Over the week the emphasis will be on understanding how computer programmers think so that participants will be able to at least participate in high-level conceptual discussions in the future with more confidence. These general concepts will be reinforced and illustrated with hands-on development of simple programs that can be used to help with text-based research and analysis right away. The language used for most of the course will be Python because of its gentle syntax and powerful extensions. Using the command-line interface and regular expressions will also be emphasized. We will also spend some time taking glimpses at what is happening in the other DHSI courses to understand how reading and writing programming code goes well beyond what we touch on in this class.

This offering is co-sponsored by ACENET.

Over the past five years we have seen a proliferation of academic job advertisements, publications, and discussions demonstrating ways in which race and social justice can be engaged in digital humanities scholarship. Interest by students and local communities in technological advancements through Web 2.0, social media, and mobile phones are permitting new forms of research and practice. #transformDH, #DHpoco, #femDH, and #BlackLivesMatter have helped to challenge the all-white discourse, often dominated by scholars in the disciplines of English and history, that is too often found in digital humanities. What happens to students in digital humanities methods classes who bring non-traditional bodies into this world? There have been discussions how to insure that syllabi and materials for digital humanities classes are inclusive – specifically, how an introductory DH methods class keeps race, social justice, and inclusivity as cornerstones in their pedagogy. The traditional divides witnessed in the tech world will only be replicated in the world of both undergraduate and graduate DH courses without attention to race, social justice, etc. This week-long class will show how, through an interdisciplinary intersectional and CRT framework, both race and social justice can be central to any DH teaching, pedagogy, and practice. The course will pay special attention to queer theory, critical ethnic studies, postcolonial theory, WOC/Black feminism, Indigenous studies, and disability studies as they currently help to reshape digital humanities teaching and methods across our university/college classrooms.

This course combines lecture, seminar, and hands-on activities.

A longstanding relationship exists between the digital humanities and writing studies as
evidenced by journals like Kairos and Computers and Composition Online; however, in
practice, the multi-faceted and mutually influential relationship between digital
technology, rhetorical theory, and interdisciplinary writing practices tends to be
underestimated. By centrally orienting this relationship, our course will explore
multimodal writing practices, theories, and pedagogies in digital spaces and reconsider
how rhetorical aims, digital platforms, and disciplinary conventions work together to
generate complex and unconventional ways of writing and opportunities for teaching.
We will consider multimodal composition across digital and analog environments,
including open-access platforms like Scalar and Twine, and we will re-purpose everyday
materials and software to reconsider rhetorical principles (like invention and
arrangement). Adopting an interdisciplinary writing studies lens, we will investigate
questions like: 

• How do we persuade and engage differently in digital and multimodal spaces? 
• How do we understand what it means to be an author and a reader in different formats or media? 
• How can we adopt co-creation and collaboration as frameworks for inclusive writing practices in digital spaces?

This course will be hands-on and will help faculty, graduate students, librarians, and
instructional technologists design assignments and activities for (digital) humanities and
interdisciplinary courses that include writing. We will collaborate on designing and
scaffolding assignments, identifying methods for assessment, and collectively
investigating the relationship between digital making tools and rhetorical practice and
pedagogy. At the end of the week, participants will have a fully designed, scaffolded
assignment and a better understanding of ways to incorporate digital writing approaches
and tools into their teaching and scholarly communication.

This class provides students with hands on experience with games and their uses in the humanities classroom. The focus of our course is to learn how games are structured, how they function and how they can become an integral part of a humanities curriculum. Participants will learn to use Twine and incorporate game narratives into their own classes. Taught by Jeffrey Lawler and Sean Smith, co-directors of the Center for the History of Video Games, Technology and Critical Play, the course covers a variety of topics such as game theory and questions that games, including tabletops and video games, raise within humanities disciplines.

This course combines lecture, seminar, and hands-on activities.

This course will focus on strategies for designing, building, and publishing long-form scholarship in fully digital formats. As we consider commonly-used platforms like Pressbooks, Omeka, and Scalar, we will discuss flexible writing workflows and best practices for developing a multimodal expressions of your research, regardless of medium. Our discussions will be guided by an audience-centered approach to project design, and the course will offer participants ample opportunities to reflect on their own research, professional goals, and audiences as they make choices about the content and layout of their own projects. This course is ideal for graduate students who are contemplating a born-digital dissertation, scholars who are working heavily with multimedia, and those who are curious to explore alternatives to print-based scholarship.

This course balances lectures with hands-on activities.

The course offers an effective hands-on intro to natural language processing (NLP), text and media analysis, and text and/or media corpus network visualization and analysis. It will harness the power and amplitude of large language models (LLMs) alongside other computing resources in analyzing both single/discrete datums and big data, be they text or media or both. The skills, affordances, methods, and concepts will be paced and assembled into a pipeline starting from locating, collecting/scraping, and (pre)processing relevant datasets, continuing by deploying specialized libraries and developing algorithms for multi-feature data analysis, and culminating with fine-grained holistic networked assemblages modeling and scrutinizing the datasets in depth and comparatively across corpora and media.

We will be doing coding in Python and learning how to use (and compare) (sub)word, text, and media modeling open-source LLMs/frameworks such as GPT (2 and later), (M)BERT, GPT-NeoX, T5, (Meta-)Llama, OLMo, and a host of others in concurrence with a wide-range of relevant libraries including Scikit-learn, NLTK, FastText, Stanza, and SpaCy (displaCy), involving embeddings with text classifiers and/or image/video/audio vectorization, e.g.., Deep Learning architectures, CLIP, MediaPipe, TensorFlow & Keras, Pytorch, LibROSA, etc. In the context, we will also learn how to train or fine-tune our own LLMs.

After using BeautifulSoup, Selenium, and pytesseract (Python-tesseract) to automatically collect and (if needed) OCR our data, the subsequent computational analyses will be translated to networks ranging from plain (single-layer) graphs to multiplexes to most general multilayer networks to be visualized and/or analyzed by means of NetworkX or, in the more specific or complex cases, in-house/indie algorithms. The translation to networks will also involve correlations between various forms of vectorization applied to text (and/as inter)media as coexistent in or combined into modeling the data.

On the fifth day (Friday, June 6th), everybody will have the opportunity to participate in the #GraphPoem event, an intermedia social computing and data-commoning performance drawing on the algorithms, methods, and programming presented or developed in class.

The knowledge and skills acquired—alongside our in-class applications—will be useful in education, research, and analytical-creative work involving NLP, automated text and (mono and multilingual) corpus analysis, network science (or graph theory) applications, inter/trans-disciplinary text (and) media studies, computational literary studies/analysis/criticism, computational linguistics, multimodal and intermedia(lity) studies and creativity, HCI creative writing and experimental/intersemiotic/literary translation, digital editions, digital poetry/e-lit/digital art, social (media/network) analysis, complexity studies in/and social science, and applications in the philosophy of mathematics.

This is a hands-on course with some lecture components.

This course introduces fundamental web and DH skills using CollectionBuilder, an open source framework for building digital collection and exhibit websites driven by metadata and hosted on a lightweight infrastructure. The high cost and IT requirements of digital collection platforms are often a barrier to creating new collections for sharing or teaching humanities research. CollectionBuilder is optimized for non-developers and simple hosting solutions, allowing researchers to take greater ownership over their digital projects and lowering barriers to customization. Scholars in this course will learn CollectionBuilder by engaging in a scaffolded approach with hands-on experience in digital library foundations such as accessibility, metadata creation, and web development. Building on these skills, students will learn the basics of working with plain text files, CSV data, Markdown, Jekyll, Git, GitHub, and GitHub Pages in order to create and customize their very own digital collection. By the end of this course, students will have gained the knowledge and independence necessary to implement CollectionBuilder in contexts that include creating and disseminating research collections and custom digital exhibits, or teaching digital libraries in the classroom. They will also have built their own digital exhibit, such as those built by our previous DHSI classes in 2023 and 2024.

No programming experience is necessary, although you should have a strong interest to learn! Participants are asked to bring their own computers. All software used in the course is free, open source, and cross platform and will be installed during class time. 

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. Just as a fighter shifts from foot to foot to be ready to counter a punch, the agile project manager constantly considers shifts to accommodate any changes in the project’s environment. But 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.

This course combines lecture, discussion, and hands-on activities. 

This course will focus on the processes and methods of digital humanities and how they intersect with librarianship practice. We will start by considering big picture questions: how have librarians approached “doing DH” and “supporting DH” in libraries, what has the practice of DH librarianship been, and what could the future of DH in libraries be? From there, we will survey different aspects of DH in librarianship in more detail, including assessment and strategic planning, reference and consultation, instruction, project management, and collaborative partnerships. Along the way, we will explore key resources, methods, and tools, as well as threshold concepts, data literacy, and relationships to other parts of academic libraries.

This course combines lecture, seminar, and hands-on activities.  

This course introduces the basic knowledge of social network analysis (SNA) to digital humanities scholars, especially historians. The course will consist of three parts. The first introduces the theory and terminology of SNA, centrality, its measurements, and other key SNA categories such as groups/subgroups, ego networks, and two-Mode networks. The second part introduces the use of SNA in historical research by reviewing the recent publication. The last part will offer a historical social network dataset for students to practice SNA research. This course will use NodeXL instead of relevant R or Python packages. 

This course will help faculty, staff, and instructional technologists conceptualize, design, and explore platforms for courses teaching book history and editorial practices. The course will provide readings on the history of the book and the book after the digital turn, and together we will discuss ways to immerse students in archival, editorial, and analytical practices regardless of their access to material books in special collections. Throughout the week, we will explore digital tools and platforms and consider how to best adapt them for the study of book history. We will collaborate on designing and scaffolding assignments, consider methods for assessment, and collectively build a repository of resources, links, and prompts. At the end of the week, participants will leave with a fully designed course unit and a better understanding of how to incorporate digital tools within their book history lessons and courses. 

This course combines lecture, seminar, and hands-on activities.

In the past, scholars applied lemon juice and a heat source when uncovering hidden features of historical documents (think: “National Treasure”). We now know that this method damaged artifacts unnecessarily. Interest in this field has led to newer, safer practices involving cameras, sensors, and LED panels. A low-cost, low barrier-to-entry Multispectral Imaging System for Historical Artifacts (MISHA) funded by NEH and developed by the course instructors and their interdisciplinary lab puts image capture and processing tools, as well as the system itself, within the reach of non-scientists. By participating in this week-long course, participants will learn a brief history of cultural heritage imaging, with an emphasis on multispectral imaging; will try their hand at capturing images and processing them; will learn of use cases where MISHA and other imaging systems have been able to illuminate content and context of manuscripts, sheet, leaf, and folia created from the medieval to the modern; and will use the MISHA system and to develop new digital humanities skills that pertain to discoverability, access, preservation, and the production of new knowledge. The intended audience is humanities scholars interested in text recovery, codicology, and imaging practices as a new and accessible DH method.

At the end of the week, participants will leave with knowledge of cultural heritage imaging’s history and theories, particularly multispectral imaging; experience using a MISHA system for image capture; familiarity with image processing methods to yield new knowledge (focusing on six sample data sets featuring collections from the medieval to the modern); and strategies of how to incorporate digital tools within their research, scholarship, and/or pedagogy.

The course combines lecture, seminar, and hands-on activities working with sheet, leaf, and folia from an “educational use” collection to demonstrate capacity of multispectral imaging as a digital humanities tool for access, discovery, interpretation, and research. 

This course is a hands-on introduction to using LLM technology (large language models like ChatGPT or Gemini) to assist with the practice of writing nonfiction. Popular discussions of this technology have focused on the unconstrained models’ tendencies to hallucinate, their inability to cite or return verifiable sources of information, and their potential misuse for misinformation and disinformation. When you are working with these models at a more technical level, however, you learn that their capabilities are changing every few weeks. As current problems are solved new opportunities and challenges arise. This course teaches ways to constrain and even make use of hallucination, to draw information and make inferences from verifiable structured data, and to rigorously cite sources. The workflows that you will learn are firmly grounded in the tools and techniques of the digital humanities: text encoding, the semantic web, linked open data, bibliography, databases, web APIs, text analysis, and text mining. There are two key differences, however. Rather than working with off-the-shelf tools or building them from the ground up, generative AI allows us to work from the top down. We also make extensive use of the models’ ability to co-author code as well as prose.

This course will require a minimal additional fee for software.

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.

Le cours a pour but de cultiver une compréhension critique des visualisations de données à la fois par l’analyse et par la pratique. Il présente les bonnes pratiques générales pour les visualisations de données, se concentre sur l’expansion de la culture visuelle à travers une variété de formes visuelles et de graphiques, et met en évidence des approches spécifiques pour les données en sciences humaines. Ces données sont comprises ici comme des données GLAM par exemple, documentant une série d’objets, tels que des œuvres d’art ou des documents d’archives, à travers des propriétés de description systématiques. Chaque participant·e créera une visualisation de données interactive avec ses propres données de recherche. Les étudiant·e·s peuvent contacter Lena Krause avant le cours et à la fin de la première journée pour s’assurer qu’iels disposent d’un ensemble de données ou d’un échantillon fonctionnel pour leur projet. Les étapes du cours comprendront la préparation et le nettoyage des données, le choix de la forme visuelle appropriée pour les données et l’objectif de recherche, et la réflexion sur les flux de données pour une édition et une publication ultérieures.

Étant donné que la visualisation de données est un domaine très vaste, cet atelier ciblera spécifiquement les visualisations de données bidimensionnelles telles que des chronologies ou des graphiques (projection des données sur un plan deux axes continus ou discrets X et Y). Compte tenu du temps disponible et afin de proposer une approche pédagogique collective, nous n’aborderons que les aspects théoriques des graphes de réseaux et de la cartographie.

Ce cours s’adresse aux chercheuses et chercheurs en sciences humaines et sociales qui n’ont aucune expérience de la programmation et qui souhaitent comprendre le fonctionnement des programmes sous le capot en écrivant eux-mêmes quelques programmes simples mais utiles. Au cours de la semaine, l’accent sera mis sur la compréhension du mode de pensée des programmeuses et programmeurs informatiques afin que les personnes participantes puissent à l’avenir contribuer à des discussions conceptuelles de haut niveau avec plus d’assurance. Ces concepts généraux seront renforcés et illustrés par le développement pratique de programmes simples qui peuvent être utilisés pour faciliter la recherche et l’analyse de textes. Le langage utilisé pour la majeure partie du cours sera Python en raison de sa syntaxe simple et de ses extensions puissantes. L’utilisation de l’interface en ligne de commande et des expressions régulières sera abordée. Nous jeterons enfin un coup d’œil sur ce qui se passe dans les autres cours du DHSI pour mieux comprendre les applications possibles de la lecture et de l’écriture de code de programmation.

Cette offre est co-parrainée par Calcul Québec