A digital ecosystem for the multidisciplinary study of Notre-Dame de Paris

De Luca, Livio

doi:10.1016/j.culher.2023.09.011

Cited by 6 publications

(3 citation statements)

References 14 publications

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“…documentation for various purposes. Drawing parallels with the Notre Dame Cathedral restoration project [30,31] in Paris, France, after the 2019 fire, showcases the effectiveness of BIM technology in preserving historical integrity and coordinating multidisciplinary efforts.…”

Section: Methodsmentioning

confidence: 97%

“…This results in a comprehensive BIM model of the Charles V Pavilion, streamlining coordination among teams, conflict detection, and precise documentation for various purposes. Drawing parallels with the Notre Dame Cathedral restoration project [ 30 , 31 ] in Paris, France, after the 2019 fire, showcases the effectiveness of BIM technology in preserving historical integrity and coordinating multidisciplinary efforts.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Integrated Building Modelling Using Geomatics and GPR Techniques for Cultural Heritage Preservation: A Case Study of the Charles V Pavilion in Seville (Spain)

Zaragoza,

Bayarri,

García

2024

J. Imaging

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This paper highlights the fundamental role of integrating different geomatics and geophysical imaging technologies in understanding and preserving cultural heritage, with a focus on the Pavilion of Charles V in Seville (Spain). Using a terrestrial laser scanner, global navigation satellite system, and ground-penetrating radar, we constructed a building information modelling (BIM) system to derive comprehensive decision-making models to preserve this historical asset. These models enable the generation of virtual reconstructions, encompassing not only the building but also its subsurface, distributable as augmented reality or virtual reality online. By leveraging these technologies, the research investigates complex details of the pavilion, capturing its current structure and revealing insights into past soil compositions and potential subsurface structures. This detailed analysis empowers stakeholders to make informed decisions about conservation and management. Furthermore, transparent data sharing fosters collaboration, advancing collective understanding and practices in heritage preservation.

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Section: Methodsmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

Integrated Building Modelling Using Geomatics and GPR Techniques for Cultural Heritage Preservation: A Case Study of the Charles V Pavilion in Seville (Spain)

Zaragoza,

Bayarri,

García

2024

J. Imaging

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“…This scientific action involves more than 175 researchers specialized in materials (stone, wood, metal, stained-glass), decoration, structural acoustics behaviors, and heritage emotions. Among them, the Digital Data Working Group (Groupe de Travail Données Numériques) is coordinating the development of a digital ecosystem aiming at managing the complete data lifecycle produced within the framework of the general scientific site (De Luca, 2024). The core technological framework of the digital ecosystem consists of a digital platform for the data centralisation (Néroulidis et al, 2024) including dedicated web services opened to more than 100 registered users for the ingestion, indexing and thematic categorisation of multimedia content, as well as for interactive analysis of 2D/3D/4D representations of architectural elements and remains.…”

Section: Contextmentioning

confidence: 99%

Strategies and Experiments for Massive 3d Digitalization of the Remains After the Notre Dame De Paris’ Fire

Comte,

Pamart,

Réby

et al. 2024

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. After the catastrophic fire at Notre Dame de Paris, a significant challenge was presented by the numerous lead-contaminated remnants. To address this, a detailed digitization strategy was devised and executed, tailored to the unique needs of this extensive and diverse corpus. This strategy involved the development and customization of both hardware and software tools, ensuring their effectiveness throughout the digitization process – from initial data acquisition to data dissemination.Central to our approach was the alignment of our methods with the distinct characteristics of each artifact, facilitating their effective preservation and future utility. Our strategy's adaptability was key, allowing us to incorporate advanced deep learning techniques into various aspects of our workflow. Notably, this included the implementation of the Segment Anything Model for automatic image segmentation, enhancing our image-based modeling capabilities. We also ventured into pioneering methods like 3D Gaussian Splatting and the exploration of radiance field methods for visualization.Moreover, the project has been mindful of data responsibility, aiming to make all digital data openly accessible beyond 2025. We have placed a strong emphasis on harmonizing and managing data, minimizing redundancies, and ensuring efficient storage, all while maintaining transparency about the limitations and errors in our methodologies. This holistic approach to digitization, balancing technological innovation with responsible data management, aims to preserve and make accessible the digital heritage of Notre Dame de Paris for future generations.

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Hybrid Construction of Knowledge Graph and Deep Learning Experiments for Notre-Dame De Paris’ Data

Réby,

Guillem,

De Luca

2024

Digital Innovations in Architecture, Engineering and Construction

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A digital ecosystem for the multidisciplinary study of Notre-Dame de Paris

Cited by 6 publications

References 14 publications

Integrated Building Modelling Using Geomatics and GPR Techniques for Cultural Heritage Preservation: A Case Study of the Charles V Pavilion in Seville (Spain)

Integrated Building Modelling Using Geomatics and GPR Techniques for Cultural Heritage Preservation: A Case Study of the Charles V Pavilion in Seville (Spain)

Strategies and Experiments for Massive 3d Digitalization of the Remains After the Notre Dame De Paris’ Fire

Hybrid Construction of Knowledge Graph and Deep Learning Experiments for Notre-Dame De Paris’ Data

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