This half-day workshop introduces textual scholars and practitioners to the LEAF Commons of tools that are web-based and easy-to-use for text encoding, named entity recognition, web annotation, and publication without users having to learn complex coding languages. LEAF supports easy movement between these interoperable tools based on users’ needs.

This paper introduces a digital database and GIS mapping project that uses ArcGIS to map and compile data from treasure-hunting excavations that occurred across the early modern Hispanic world.The project will be hosted publicly, allowing users to gain a better sense of premodern disturbances of the archaeological record.

This paper presents an interactive visualization platform and ETL pipeline for mapping institutional networks in digital cultural heritage. By analyzing data from multiple sources, including funding patterns and research outputs, the system enables humanities scholars to examine institutional power dynamics and supports evidence-based decision making for cultural heritage initiatives.

In this paper we present findings from a new crowdsourced resource - Speak for Yersel - which sets out to map dialect use in Scots throughout Scotland. How successful is crowdsourcing in revealing Scots in all its complex dialect guises?

Maps have their own visual grammar that combines graphical and textual elements in a unique form of meaning-making that is both multimodal and geospatial. We introduce a multimodal approach that allows us for the first time to approach text on maps as research data in its own right.

Novel openings’ similarities and differences raise literary-historical questions. With our contribution, we aim to advance that research by means of digital text annotation and spatiality analysis of the openings of a selection of 19th and 20th century novels in German and Spanish.

Our project combines AI with citizen science to examine whether Japanese early-modern print (ukiyo-e) illustrators created landscape prints from direct observation or secondary sources. Using fine-tuned vision language models, GIS mapping, and crowdsourced spatial analysis, we authenticate artistic observation practices using historical and contemporary geographical data.

This project uses NER and digital mapping to preserve and explore the cultural heritage of the Baltic Germans. By analyzing the historical newspaper "Baltische Briefe" and visualizing historical locations, it provides an interactive platform to uncover geographical patterns and cultural narratives, demonstrating the potential of digital humanities for cultural preservation.

This paper explores the use of digital mapping to represent Colombian diasporas in New York and London, addressing the stigmatizing impact of hegemonic portrayals linked to the drug trade. By layering these narratives with counter-discourses, the project promotes a more nuanced, community-driven approach to history-making and knowledge democratization.

This paper examines Soviet nuclear testing in Central Asia using geo-technologies to map and analyze test sites' environmental and social impacts. By integrating GIS, archival records, and survivor testimonies, the study uncovers Soviet environmental colonialism, highlighting its lasting ecological and cultural consequences. It demonstrates geo-technologies’ role in historical and ecological justice.

This panel will explore how the construction of datasets about named enslaved individuals and the publication of those datasets online has allowed historians to reach new audiences and to draw new conclusions about both the collective and individual agency of enslaved people.

This study investigates the use of computational audio analysis to examine ideological narratives in Nazi propaganda films. Employing a three-step pipeline—speaker diarization, audio transcription, psycholinguistic analysis—it reveals ideological patterns in characters. Despite current issues with speaker diarization, the methodology provides insights into character traits and propaganda narratives, suggesting scalable applications.

The Chromobase depicts how the new colouring materials and techniques invented in the 1850s brought about new ways of thinking about colour in literature, art, and the history of science and technology. We present a narrative-driven methodolody and a writing-publication web application which depicts this 19th century “Colour Revolution”.

The European Commission's 2021 guidance urged accelerated digitisation of cultural heritage but noted a digital skills gap among professionals. This study examines the digital divide in cultural heritage institutions on small Mediterranean islands, proposing Open Educational Resources (OERs) to address professionals’ needs. Quantitative and qualitative analyses inform actionable, tailored solutions.

In 2022 FSU's Research Computing Center established the Interdisciplinary Data Humanities Initiative (IDHI) to foster and support the use of advanced digital tools in the humanites, social sciences, and the arts. Here we will describe our curricular efforts and workshops specificaly covering the use of high-performance computing in our classrooms.

This paper explores digital education for pupils in a humanities teaching-learning lab. The aims of this article are (a) to present initial results on the participation of pupils in Digital Humanities projects by university students and (b) to reflect digital tools in humanities education programmes for pupils.

This project, developed by the University of Foggia and Istituto Dante Alighieri, aimed to enhance students' digital and communication skills through podcast creation. The initiative combined technical workshops with creative writing, fostering critical thinking, teamwork, and civic awareness. Results showed significant improvement in media literacy and active citizenship skills.

This research presents an AI-supported scaffolded learning platform for teaching Python to Digital Humanities master's students at the University of Bologna. The system combines LLM-generated exercises and personalized feedback, addressing the unique challenges humanities students face in learning programming.

This short paper asks: what can be discovered about the poetess tradition of nineteenth-century Britain–a mode of writing initially lost to literary history and recovered by feminist literary scholars–when using topic modelling to conduct a distant reading of primary, critical, and bio-critical materials?

Picture book covers carry abundant visual information about the story. They also indicate gender information through titles and illustrations, which might further impact preschool children’s gender perception. This paper will investigate how ChatGPT infer gender on covers of 6,629 preschool children’s books from the 2012-2022 National Library of China catalogue.

This presentation will introduce the work conducted by “The Adaptive Text Encoding Initiative Network,” an interdisciplinary research group of PhD students, faculty, and DH librarians in Canada. We will report on our progress as a team and provide insights into our proposed antiracist, decolonial, and inclusive TEI guidelines.

This study examines gendered communication in German-speaking Twitch gaming chats using BERTopic and qualitative analysis. Male streamers’ chats focus on gaming, while female streamers evoke social and emotional messages. No evidence of objectification was found, highlighting shifts in behavior or effective moderation. Findings underscore gender’s role in shaping digital interactions.

This talk explores how documentation can serve as a powerful tool for positive change by making our research and datasets more transparent. Detailed documentation not only facilitates the effective and responsible reuse of datasets and algorithms but also promotes more inclusive scholarship and ethical research outcomes.

The project marks the second phase of digitizing Tolstoy’s legacy, expanding beyond the 90-volume collection. It focuses on seven sources, each reflecting the writer’s life and works, connected by common temporal points. We discuss the preparation, markup, and presentation of over 32,000 documents through an interactive interface.

The project Auden in Austria Digital explores novel methods of formalizing interpretation in scholarly digital editions by embedding RDFa within TEI/XML. By transforming editorial argumentation into machine-readable data, the project seeks to make interpretation, interpretational responsibility, and scholarly uncertainty accessible to computational processing.

This project reevaluates the historiographical practices of Dai Nihon Shiryo, focusing on the functional representation of Bouchū (marginal notes) and Warichū (interlinear annotations) using TEI. By addressing their embedded temporal semantics and editorial distinctions, this study uncovers implicit historical perspectives and contributes to advancing TEI applications in digital scholarly editing.

This paper presents the open-access semantic edition-archive of Cesare Pavese’s literary and documentary heritage, developed within the PAVES-e project. It employs the CHROMA model, incorporating XML-TEI encoding, ontology-driven semantic organization, and interactive visualization tools to facilitate enhanced accessibility and semantic and lexicographic analysis of Pavese’s works.

This paper focuses on the modeling of the digital critical edition of a collection of Aesopic fables entitled Isopet 1-Avionnet, dating from the late 13th and early 14th centuries. It will notably involve translating, into the XML/TEI encoding of this collection, the textual, rhetorical, narrative and intertextual structures of this text.

This study utilizes phonotextual and cartographical perspectives to analyze Guangzhou Bamboo Branch Poetry, exploring emotional expressions and cultural landscapes. By examining textual features and Cantonese phonetics, we reveal the interplay of history, landscape, and local customs, highlighting the genre's significance in documenting urban life and cultural evolution.

This study explores scene change detection in 20th-century US-American romance fiction using manual annotations and automated methods. Manually annotated novels build the training data for fine-tuning an English BERT USE model, yielding promising preliminary results for automated text segmentation in computational literary studies.

This paper explores ways of representing the complex ways that landscapes can be described and how this changes over time drawing on the concepts of ‘picturesque’ and ‘wild’ in the English Lake District. It evaluates a range of approaches to landscape description and perceived nearness and how these changed over time.

This paper focuses on improving art-historical image search engines by combining Vision-language Models (VLMs) with knowledge graphs. The approach intends to enhance the interpretability and accuracy of search results by using triplets extracted from domain-specific knowledge with generative models. Providing this information to the user thus also increases the transparency of AI methods.

Cette communication présente une interface de recherche pour étudier la réception de l'art public au Québec avec les données générées par les utilisateur·rice·s de l'application MONA. L’outil développé optimise l'exploration et l’analyse des expériences artistiques recueillies pour contribuer de nouvelles perspectives sur l'interaction citoyenne avec l'art public.

In this study, we leverage two open datasets, respectively representing a dictionary of art symbols and scholars’ interpretations of ca. 400 artworks, to analyse how symbols and meanings vary in the art history hermeneutic discourse. Results show that the majority of scholar’s interpretations that could be aligned use conventional symbolism.

Our contribution examines methods for capturing spatial information from historical thematic maps depicting level of destruction during the second world war, focusing on the German city of Nuremberg (Nürnberg). We demonstrate three ways of capturing information from historical thematic maps, ranging from manual to semi-automated methods.

Using freely available data, this presentation tries to characterise the romance genre in the first half of the 20^th century and to map the part women screenwriters played in its evolution.

The paper explores the role of maps as epistemic tools in the Stadt.Geschichte.Basel project, emphasizing how spatial data dynamics and moments of disconcertment foster interdisciplinary collaboration. By embracing ambiguity and conflict in map-making, the authors create accessible, inclusive outputs that reimagine historical narratives and advance participatory scholarship.

This study employs digital humanities methods and hierarchical hexagonal spatial indexing (H3) to analyze patterns of police violence against African Americans across the United States. Using Local Moran's I statistics on over 13,000 incidents between 2015-2024, it identifies significant geographic clusters and transition zones, revealing how policing practices vary across jurisdictional boundaries.

This paper presents a case study of a data visualization involving the Trans-Atlantic Slave Trade Database. We explain how theories about historical trauma and the limits of recovery guided our work. We describe our design process, and propose a series of questions that can guide future visualizations of sensitive data.

FAIR principles guide best practice for research data management. FAIR means Findable, Accessible, Interoperable, and Reusable. To reuse digital objects, one needs to have full provenance information on the object and its metadata. This paper presents two approaches for tracking metadata changes. One uses Git, the other PID features.

How accurate is the work done by the volunteers who do most of the work on crowdsourcing projects in cultural heritage? We analyze the results of the 1970 MIssouri Death Certificate indexing project, applying traditional quality metrics from Optical Character Recignition and Handwritten Text Recognition to human-created text.

Aborda o uso do software Transkribus para transcrição de documentos históricos no ensino.

The paper discusses approaches to include retrocomputing and computer laboratories into Digital Humanities practice for research, didactics, preservation and self-reflection.

Le biblioteche moderne si configurano come spazi multifunzionali, dove fisico e digitale convergono per favorire creatività, confronto e inclusione. Attraverso servizi innovativi e collaborazioni strategiche, promuovono accessibilità e partecipazione, valorizzando diversità e competenze per abbattere barriere e stereotipi, con l'obiettivo di costruire una società equa e inclusiva.

This study compares humans and AI in recreating a three-panel Nancy cartoon. Humans, with basic art training, excelled in creating coherent visual narratives, while AI, despite impressive artistic replication, struggled with storytelling. The results highlight human superiority in transforming instructions into meaningful stories.

This paper introduces a multidimensional similarity search tool, Motif-Match, for digital art history, emphasizing similarity as multi-dimensional, cumulative, and situational. Through participatory design and user evaluation with 39 participants, we explore the roles of control and transparency, offering insights into balancing technical innovation with the nuanced needs of humanities research.

Focusing on predictive algorithms and AI technologies in law enforcement, this paper argues that a digital humanist inquiry of the historical development of law enforcement in the United States is necessary for identifying how emerging policing technologies perpetuates systemic harm against marginalized communities by design.

We investigate the effectiveness of LLMs in evaluating text similarity, a fundamental task in CH research. We study the similarity of German poems from different perspectives, such as content or form. Our results show that recent commercial models are comparable to or better than supervised models (zeroshot, chain of thought).

This study employs natural language processing and machine learning to analyze religious trajectories in Holocaust survivor testimonies. Utilizing large language models, we reveal patterns of evolution in beliefs and practices under extreme conditions, offering insights into thematic narrative development and demonstrating the transformative potential of computational methods in historical analysis.