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From Archives to Networks: Data Modeling for Mapping Performance History at the Festival d'Avignon
No full textInternational audienceThe digital turn in theatre and performance studies has led to numerous databases documenting performances, productions, and artistic collaborations (Roussillon and Schuwey 2020; Oort and Noordegraaf 2020, Douguet 2024). However, the lack of standardization and interoperability between these resources limits their potential for comprehensive research in performance historiography. This paper presents an ongoing work from the ERC-funded project From Stage to Data, the Digital Turn of Contemporary Performing Arts Historiography (STAGE) which develops an approach to modeling performing arts data through linked open data principles. Using the Festival d'Avignon – one of the world's most significant performing arts events and "agora of European theatre" (Banu and Tackels 2005) – as our primary case study, we demonstrate how data modeling can reveal previously invisible patterns in artistic collaboration. With over 2,000 performances staged by international companies since its inception, the festival serves as an ideal laboratory for examining the evolution of contemporary performing arts practices and networks. Our research addresses three key methodological challenges in performing arts analytics (Bardiot 2021). First, we examine how traditional archival sources like theater programs can be transformed into structured data while preserving their historical and cultural complexity. Second, we analyze the limitations of existing data models in capturing the ephemeral and collaborative nature of performance practice. Third, we propose an extension of the Linked Art ontology that specifically addresses the needs of performance documentation and analysis, building upon initiatives in performing arts data modeling (Bollen 2016, Peyre, Amarger, and Chauvat 2024). Drawing from Actor-Network Theory (Latour 2005), and through specific examples from the Festival d'Avignon archive, we show how this approach enables new forms of historical analysis. Our model reveals patterns in artistic circulation, traces the development of performance practices, and maps the evolution of creative networks across time and space. This methodology opens new possibilities for studying how artistic communities form and evolve, and how cultural institutions shape the development of contemporary performance practices. Beyond its immediate application to the Festival d'Avignon, our research wishes to contribute to broader discussions about data modeling in theatre and performance studies. By combining computational methods with traditional historiographical approaches, we aim to demonstrate how digital tools can enhance our understanding of performance history while respecting the complexity and nuance of theatrical practice
From Stage to Data : Ontologies for Performing Arts and Linked Open Data
No full textInternational audienceThe representation and interconnectivity of performing arts data pose significant challenges due to their inherent complexity. As part of the ERC-funded project From Stage to Data, the Digital Turn of Contemporary Performing Arts Historiography (STAGE), this study investigates the development of an ontology capable of ensuring interoperability between existing ontologies and databases, with a specific focus on the adoption of linked open data principles and the Linked Art ontology, which is built upon the CIDOC CRM framework. By addressing these challenges, the project aims to unify fragmented datasets, enhance the discoverability of performing arts data, and foster interdisciplinary research
Accompagner les usagers vers l’IA : défis et motivations des bibliothécaires-“explorateurs” de l’enseignement supérieur
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L’espace du blanc dans la bande dessinée, un générateur de formes ?
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Evaluation of the textual responses of systems (Questions/Answers) of the engines (Bing.com and Yandex.com) and Chat-GPT: Access to textual data, via monolingual questions.
No full textInternational audienceThis article covers querying when a user queries a traditional search engine (www.Bing.com ; www.Yandex.com ) or Chat-GPT in a language other than the language of the documents sent by the index. That is to say, do a search with a question in “English” on a french language search engine on its “French” linguistic index and on the index of in order to compare results with ChatGPT AI engin
