The Historic Urban Landscape Approach in Edinburgh’s Old and New Towns: Implementation of Projects on the Ground in a Living Capital City

Wilkinson, Adam

doi:10.1007/978-981-10-8887-2_12

Cited by 1 publication

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“…Following the Burra Charter and the Recommendation of HUL, the practice of heritage management, previously dominated by the authorised discourse, is transforming towards a more inclusive, dynamic, and diversified alternative. In this light, recent studies about the cultural significance and heritage management touch upon topics including public and community participation , adaptive reuse and redesign as interventions Yarza Pérez and Verbakel, 2022;, people-centred heritage (Liu, 2011;Liu et al, 2019;, consensus building (Wilkinson, 2019;, integration with spatial planning and policy-making Sánchez et al, 2020;, monitoring the urban dynamic globally Verbruggen et al, 2014;, and so on.…”

Section: Cultural Significance and Heritage Managementmentioning

confidence: 99%

Sensing the Cultural Significance with AI for Social Inclusion

Bai

2023

Architecture and the Built Environment

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Social Inclusion has been growing as a goal in heritage management. Whereas the 2011 UNESCO Recommendation on the Historic Urban Landscape (HUL) called for tools of knowledge documentation, social media already functions as a platform for online communities to actively involve themselves in heritage-related discussions. Such discussions happen both in “baseline scenarios” when people calmly share their experiences about the cities they live in or travel to, and in “activated scenarios” when radical events trigger their emotions. To organize, process, and analyse the massive unstructured multi-modal (mainly images and texts) user-generated data from social media efficiently and systematically, Artificial Intelligence (AI) is shown to be indispensable. This thesis explores the use of AI in a methodological framework to include the contribution of a larger and more diverse group of participants with user-generated data. It is an interdisciplinary study integrating methods and knowledge from heritage studies, computer science, social sciences, network science, and spatial analysis. AI models were applied, nurtured, and tested, helping to analyse the massive information content to derive the knowledge of cultural significance perceived by online communities. The framework was tested in case study cities including Venice, Paris, Suzhou, Amsterdam, and Rome for the baseline and/or activated scenarios. The AI-based methodological framework proposed in this thesis is shown to be able to collect information in cities and map the knowledge of the communities about cultural significance, fulfilling the expectation and requirement of HUL, useful and informative for future socially inclusive heritage management processes.

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Section: Cultural Significance and Heritage Managementmentioning

confidence: 99%

Sensing the Cultural Significance with AI for Social Inclusion

Bai

2023

Architecture and the Built Environment

View full text Add to dashboard Cite

show abstract

The Historic Urban Landscape Approach in Edinburgh’s Old and New Towns: Implementation of Projects on the Ground in a Living Capital City

Cited by 1 publication

References 2 publications

Sensing the Cultural Significance with AI for Social Inclusion

Sensing the Cultural Significance with AI for Social Inclusion

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