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Digitized or born-digital, digital sources are one of the most significant challenges facing performing arts historiography: they are fragile (technological obsolescence), multimodal (texts, images, videos, programs), and numerous (big data). Think, for example, about the 20,000 photographs taken each year by the official photographer of the Festival d'Avignon; or the 15,000 files documenting the creation process of one work. Digital traces are the future of performing arts studies and our new primary sources. The shift to digital not only transforms the nature of our sources but also reshapes how research is conducted and its outcomes. How can we interpret digital traces? How can we “make them talk”? What new insights can we draw from them? STAGE tackles these questions head-on by offering a theoretical and methodological framework situated at the confluence of history, epistemology, and digital humanities. Drawing from the Festival d'Avignon collection and employing interdisciplinary methodologies, we aim to renew performing arts studies and demonstrate the profound significance of digital traces in both preserving and analyzing our cultural heritage. By leveraging the advancements in digital humanities and artificial intelligence, we uncover new insights into the historical and aesthetic dimensions of mise en scène since WWII. Through the two prisms of resurgence and collaboration, STAGE endeavors to reveal creation contexts and networks, aesthetic reminiscences and creative process models. This approach lays the groundwork for what we term "performing arts analytics."
Ivo Van Hove, Les Damnés, 2016 © Christophe Raynaud de Lage
STAGE, spanning from January 2024 to December 2028, delves into a pivotal moment of transformation: the transition of traditional sources into digital traces. This paradigm shift alters the nature of historical sources, operating on both hermeneutic and epistemological levels. Digital technology transforms traces into data, inviting us to reconsider traditional research approaches in performing arts studies. To build these methods and demonstrate their potential, we will rely first on a corpus that has not yet been explored at this scale and which offers a particularly fertile field to approach such questions: the archives of the Festival d'Avignon, before opening to broader corpora in a second phase in order to scale up our results and expand our analysis. Bridging qualitative and quantitative research approaches, STAGE focuses on three intermediate objectives:
1) To visualize performing arts , by creating a network using data from programs to showcase interactions among thousands of individuals, different forms of artistic and technical collaborations as well as the context of creation over time. This approach, drawing on actor-network theory, will lead to an updated perspective of the rich and complex context of contemporary European stagings. However, a crucial challenge lies in the absence of a universal standard for describing performing arts. STAGE plans to address this by creating an ontology to enhance description and facilitate interoperability with other collections and datasets.
2) To reveal staging intertextuality . Photographs and videos are crucial traces in performing arts, enabling "distant viewing". By applying intertextuality to stage imagery, we unveil complex relationships with past performances, identifying resurgences and connections. Advances in computer vision facilitate the development of an iconology of performing arts, tracing aesthetic networks. STAGE will contribute to the training and development of computer-vision algorithms dedicated to performing arts.
3) To model creative processes , taking into account not only the rehearsals but also all the data produced by all the team members. The computational analysis of performances' creative process, particularly their collaborative dimension, presents significant challenges in performing arts studies. Digital traces, often ignored in actual research on creative processes, offer new opportunities by capturing the entire creation process, from initial ideas to premiere. By developing a multimodal environment to collect and analyze data from 15 performances, STAGE will renew the study of creative processes. This approach will unveil unique insights into the diversity of performing arts practices.
News
- Call for Papers -
Call for papers, end of submissions: 01 / 12 / 24. Event date: 24 - 25 / 01 / 25.
- Event -
09 / 09 / 24: Five presentations will be aiming to address the challenges and opportunities associated with the use of digital data for art studies.
- Event -
09 / 09 / 24: STAGE is organizing a day of discussions focused on ontologies and their application to the performing arts.
- Publication -
20 / 06 / 24 : During the month of June, our team members participated in two conferences : DH Benelux 2024 and the Annual IIIF conference.
Team
The STAGE team brings together a multidisciplinary group of researchers, PhD candidates, data and software engineers collaborating across areas such as performing arts history, digital humanities, genetics studies, machine learning, and computer vision.
Clarisse
Bardiot
http://www.clarissebardiot.info/
Clarisse Bardiot, STAGE project PI, is Professor of history of contemporary theatre and digital humanities at Rennes 2 University. Her research focuses on performing arts digital traces, creative processes analysis, the history and aesthetics of digital performance, the preservation of digital works, and experimental publishing. She is the author of Performing Arts and Digital Humanities. From Traces to Data (Wiley / Iste, 2021).
Jacob
Hart
Jacob Hart is currently a postdoctoral researcher on the MemoRekall Project at Université Rennes 2, France. He obtained his PhD in musicology at the University of Huddersfield (UK) in 2021 where I was a member of the ERC-funded FluCoMa Project (Fluid Corpus Manipulation). His research centres around tracking the creative process of techno-fluent composers and developing new approaches to computational musicology.
Jeanne
Fras
Jeanne Fras joined the project soon after graduating from a master's degree in Digital Humanities at the Centre d'Etudes Supérieures de la Rennaissance (CESR) in Tours, occupying the position of Data Engineer. Before that, she participated in the Archival City project in Université Gustave Eiffel as an intern.
Xhensila
Lachambre
Xhensila Lachambre, project manager: she supports the PI and its team in the implementation of the STAGE project. Since 2019, she has been working on supporting Rennes 2 European projects funded by programmes such as Horizon 2020, LIFE, COST, CERV, etc.
Théo
Heugebaert
Théo Heugebaert is a PhD candidate in creative research in theater studies at Rennes 2 University. Under the supervision of Sophie Lucet and Clarisse Bardiot, he is working on the concept of rhythm in performing arts, focusing particularly on how the rhythm of a form is conceived, revealed, and structured during its creation process.
Claire
Assadi
Claire Assadi is an intern on the project. She is currently in her second year of a Master's program in International Relations, Globalization, and Interculturality . This curriculum is supplemented with a Master's in Digital Humanities. Her master thesis focuses on actor networks in cultural diplomacy. She mostly participates in the development and coding of a pose detection program.
Nicolas
Foucault
Nicolas Foucault holds a PhD in Computer Science specializing in Natural Language Processing (NLP). He is a Data Scientist on the STAGE project. He has worked as a CNRS researcher at the Cité des Sciences in Paris and at MoDyCo on the first two #MuseumWeek’s editions in partnership with Twitter and the French Ministry of Culture and Communication. As an engineer, he worked on the automatic classification of emails using neural networks in the European research project MAIVA which he co-launched with Télécom Saint-Etienne while working at Julie Desk.
Antonios
Lagarias
Antonios Lagarias is a PhD candidate in theatre studies and digital humanities at Rennes 2 University, under joint supervision with the University of Montréal. He holds an MA in art studies from the École Normale Supérieure-PSL (Paris-Ulm) and a degree in civil engineering from the Aristotle University of Thessaloniki. He is also a film critic, member of the FIPRESCI, and a regular contributor to the East European Film Bulletin. His current research focuses on the digital archives of the festival Off Avignon.
Alexandra
Beraldin
Alexandra Beraldin is a doctoral student in theatre studies and digital humanities at Université Rennes 2, in cotutelle with Université de Montréal. She holds a degree in theater and Italian language from the University of Ottawa and a master's in theatre studies from Université Paris VIII. Alexandra is also a translator, theater critic and movement director. Her current research focuses on digital traces and creative processes.
Associate Researchers
Bernard
Jacquemin
https://pro.univ-lille.fr/bernard-jacquemin
Bernard Jacquemin is a researcher and lecturer at the University of Lille, within the GERiiCO laboratory. His work falls within the field of digital humanities and focuses particularly on the study of natural information and its appropriation by computer systems, the representation of knowledge and heritage data in the semantic web, the ethical and critical analysis of the platformization of open science, the collaborative construction of encyclopedic information, and the computational modeling of human language. In recent years, he has participated in various research projects such as ANR MémoMines (heritage of coal mines), ANR Dorémus (musical data), and Tectoniq (heterogeneous documents related to textile heritage). He teaches in various programs related to library, archival, and more generally, information and documentary data professions.
Aurélie
Lemaître
https://perso.univ-rennes2.fr/aurelie.lemaitre.legargeant
Aurélie Lemaitre is Professor in computer science at Université Rennes 2, France. She is member of the Shadoc team of IRISA lab. Her research focuses on the analysis of images of documents, and particularly document layout analysis. She works on the different ways to combine deep learning approaches and syntactical rules for the recognition of images.
