Decoding the Knowledge Space of 'Architectural and Urban Traditions' Utilising a Metadata Framework

Madhavi P. Patil, Ashraf M. Salama*, Tarek M. F. Ahmed

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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Abstract

This article explores the discourse on Architectural and Urban Traditions (AUT), examining its evolution expressions, and manifestations as a knowledge space. Utilising a Metadata Framework (MF) based on six lines of inquiry–scale, discipline, geographical diversity, typology, governance, and investigation methods–this research systematically examines the relationship between various research dimensions as perceived, researched, and interpreted by academics and scholars. It involves text mining and content analysis to enable deeper, data-driven exploration of evolving themes and patterns within the AUT knowledge space. The MF is implemented through the case of the International Association for the Study of Traditional Environments (IASTE), which is identified based on its focus and longstanding contribution to the discourse since the late 1980s. The study demonstrates how the two pillars of IASTE–Traditional Dwellings and Settlements Review (TDSR) and the biennale conferences (recently annual conferences) have shaped the discourse on traditional environments. It primarily contributes to the field by advancing the application of the Metadata Framework (MF) as a systematic tool for mapping the evolution of AUT discourse, providing valuable insights for future research. Key findings reveal a significant rise in technological integration and governance studies, sustained interest in studying intangible cultural heritage, and growth in linking this with advanced technologies. Conclusions are drawn to elucidate evolving, emerging, and declining themes and areas within the overall knowledge space of architectural and urban traditions.
Original languageEnglish
Pages (from-to)37-56
Number of pages20
JournalJournal of Architecture and Urbanism
Volume49
Issue number1
DOIs
Publication statusPublished - 25 Feb 2025

Keywords

  • knowledge space
  • text-mining
  • architectural and urban traditions
  • metadata framework
  • architectural
  • urban traditions

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