Skip to main content

ORIGINAL RESEARCH article

Front. Big Data
Sec. Data Mining and Management
Volume 7 - 2024 | doi: 10.3389/fdata.2024.1309887
This article is part of the Research Topic Visualizing Big Culture and History Data View all 5 articles

Cultural Big Data: Nineteenth to Twenty-first Century Panoramic Visualization

Provisionally accepted
  • Swiss Federal Institute of Technology Lausanne, Lausanne, Vaud, Switzerland

The final, formatted version of the article will be published soon.

    From the nineteenth-century panorama to the emergence of the digital panoramic format in the 1990s, the visualization of large images frequently relies on panoramic viewing strategies. Originally rendered in the form of epic painted canvases, these strategies are now amplified through gigapixel imaging, computer vision and machine learning. Whether for scientific analysis, dissemination, or to visualize cultural big data, panoramic strategies pivot on the illusion of immersion. The latter is achieved through human-centered design situated within a large-scale environment combined with a multi-sensory experience spanning sight, sound, touch, and smell. In this article, we present the original research undertaken to realize a digital twin of the 1894 panorama of the battle of Murten. Following a brief history of the panorama, the methods and technological framework systems developed for Murten panorama's visualization are delineated. Novel visualization methodologies are further discussed, including how to create the illusion of immersion for the world's largest image of a single physical object and its cultural big data. We also present the visualization strategies developed for the augmentation of the layered narratives and histories embedded in the final interactive viewing experience of the Murten panorama. This article offers researchers in heritage big data new schemas for the visualization and augmentation of gigapixel images in digital panoramas.

    Keywords: Big Data1, Panorama2, Battle of Murten3, Gigapixel image4, Data visualization5, 3D Augmentation6, Media Archaeology7, Cultural History8

    Received: 08 Oct 2023; Accepted: 04 Sep 2024.

    Copyright: © 2024 Chau, Hibberd, Jaquet and Kenderdine. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Sarah I. Kenderdine, Swiss Federal Institute of Technology Lausanne, Lausanne, 1015, Vaud, Switzerland

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.